Image Orientation

This study delves into U.S. catfish consumer behavior in the Southern USA, utilizing a comprehensive online survey encompassing 2,129 participants across ten states. Employing rigorous statistical analysis, including regression and multinomial logistic regression, the research dissects the intricate interplay of socioeconomic variables, cultural influences, and personal preferences. Significant findings indicate a discernible shift in preferences towards fresh catfish, reflective of an evolving seafood consumption landscape. Noteworthy impacts of seafood branding, recipe information, and resealable packaging on consumer behavior further underscore the involvedness of decision-making. Crucially, socio-demographic factors such as age, gender, income, education, and occupation emerge as pivotal determinants of catfish consumption frequency, providing valuable insights for targeted marketing. Implications extend to policymakers, industry stakeholders, and researchers in aquaculture economics. Recommendations advocate for tailored marketing strategies that consider regional nuances, sociodemographic intricacies, and evolving consumer preferences. Integrating customized marketing, supply chain management, and pricing strategies is poised to address the diverse preferences of consumers across varied regions.

In recent years the research activity in image registration has grown at the same pace as the high resolution satellite images have found their way to end users. Much of this research activity has concentrated on methods improving the accuracy of georeferencing provided as RPC values. In this study the image registration via projective transformation based on straight line segments is investigated. The transformation parameters are solved based on real data extracted from topographic database and measurements done on QuickBird image. Same data is processed also with point wise method and accuracy numbers in selected check points are calculated. The RMS values computed in same check points prove that with the line based method the equivalent accuracy can be achieved as with the point wise method computed with minimum number of observations. In a smaller sub image the accuracy of transformation with line segments could be verified to be in size of a pixel.

ABSTRACT: The physical and generalized sensor models are two widely used imaging geometry models in the photogrammetry and remote sensing. Utilizing the rational function model (RFM) to replace physical sensor models in photogrammetric mapping is becoming a standard way for economical and fast mapping from high-resolution images. The RFM is accepted for imagery exploitation since high accuracies have been achieved in all stages of the photogrammetric process just as performed by rigorous sensor models. Thus it is likely ...

There is a strong competition from low-priced imported catfish fillets resulting in a declining market share for domestic farm-raised catfish fillets. To match the competition, catfish processors are embarking on pricing policy measures that are volume-oriented instead of profitor image-oriented. This could be an effective short-run pricing policy measure for optimal longrun sustainability and profitability of the industry. Volume pricing strategies are aimed at meeting target sales volumes or market shares. This paper explores and compares the performance of the standard logit, the inverse power transformation (IPT) logit and the logarithmic version of the inverse power transformation logit models in terms of generating forecasts for market share of U.S. farm-raised catfish fillets. The results suggest a better performance of the log-IPT in every aspect compared to the linear standard logit and the IPT logit models.

The purpose of this study was to examine the comparability of morphometric measurements made on pediatric data sets collected at five scanner locations, each using variations on a 3D spoiled gradient-recalled echo (SPGR) pulse sequence. Method: Archived MR data from 60 typically developing children were collected and separated into seven groups based on the pulse sequence used. A highly automated image-processing procedure was used to segment the brain data into white tissue, gray tissue, and CSF compartments and into various neuroanatomic regions of interest. Results: Volumetric comparisons between groups revealed differences in areas of the temporal and occipital lobes. These differences were observed when comparing data sets with different image orientations and appeared to be due to partial volume averaging (PVA) and susceptibility-induced geometric distortions. Conclusion: Our results indicate that slice selection and image resolution should be controlled in volumetric studies using aggregated data from multiple centers to minimize the effects of PVA and susceptibility-induced geometric distortions.

To meet the high frame rate requirements of correct point correspondences with a sub-pixel precision, this paper first proposes a Field Programmable Gate Array (FPGA) architecture that consists of corner detection, corner matching, outlier rejection, and sub-pixel precision localisation. In the architecture, a combined Features from Accelerated Segment Test (FAST)+ Binary Robust Independent Elementary Features (BRIEF) algorithm is adopted for detection and matching with pixel precision, a combined algorithm of Slope-based Rejection (SR) and Correlation-Coefficient-based Rejection (CCR) is used to reject the outliers, and a gradient centroid-based algorithm is used for subpixel precision localisation. The whole FPGA architecture is implemented on a single FPGA platform (Xilinx XC72K325T). Five image datasets with different spatial resolutions, textures, lights, rotate angles, and viewpoints are used to evaluate the performance of the FPGA-based implementation. The experimental results show that (1) the SR and CCR algorithms are effective for outlier rejection; (2) a higher correct matching rate is achieved for the image pairs that cover artificial textures than for those that cover natural textures; (3) the proposed architecture is also suitable for image pairs with small change of lights, rotate angles, and viewpoints; (4) the speed of the FPGA-based implementation can reach 280 Frames Per Second (FPS), which is 35 times faster than the Personal Computer (PC)-based implementation; and (5) the usage of FPGA resources is acceptable for the selected FPGA platform. The speed and usage of the FPGA resources can be improved when the whole FPGA-based implementation is further optimised.

This study examined how cells in the temporal cortex code orientation and size of a complex object. The study focused on cells selectively responsive to the sight of the head and body but unresponsive to control stimuli. The majority of cells tested (19/26, 73%) were selectively responsive to a particular orientation in the picture plane of the static whole body stimulus, 7/26 cells showed generalisation responding to all orientations (three cells with orientation tuning superimposed on a generalised response). Of all cells sensitive to orientation, the majority (15/22, 68%) were tuned to the upright image. The majority of cells tested (81 %, 13/16) were selective for stimulus size. The remaining cells (3/16) showed generalisation across four-fold decrease in size from life-sized. All size-sensitive cells were tuned to life-sized stimuli with decreasing responses to stimuli reduced from life-size. These results do not support previous suggestions that cells responsive to the head and body are selective to view but generalise across orientation and size. Here, extensive selectivity for size and orientation is reported. It is suggested that object orientation and size-specific responses might be pooled to obtain cell responses that generalise across size and orientation. The results suggest that experience affects neuronal coding of objects in that cells become tuned to views, orientation, and image sizes that are commonly experienced. Models of object recognition are discussed.

We propose a new approach for tracking the cardiac motion by using simultaneously short-axis and long-axis MR images in non-rigid registration. The fusion of two image orientations allows to track more precisely the basal and apical movement of the ventricles. In addition, the motion of the atria is tracked. Correlation coefficients were 0.94 at the systolic phase and 0.97 at the diastolic phase as the volumes of manually and automatically detected chambers were compared. The results were obtained using 7 subjects.

This paper investigates the use of different greyscale conversion algorithms to decolourize colour images as input for two Structurefrom-Motion (SfM) software packages. Although SfM software commonly works with a wide variety of frame imagery (old and new, colour and greyscale, airborne and terrestrial, large-and small scale), most programs internally convert the source imagery to singleband, greyscale images. This conversion is often assumed to have little, if any, impact on the final outcome. To verify this assumption, this article compares the output of an academic and a commercial SfM software package using seven different collections of architectural images. Besides the conventional 8-bit true-colour JPEG images with embedded sRGB colour profiles, for each of those datasets, 57 greyscale variants were computed with different colour-to-greyscale algorithms. The success rate of specific colour conversion approaches can therefore be compared with the commonly implemented colour-to-greyscale algorithms (luma Y'601, luma Y'709, or luminance CIE Y), both in terms of the applied feature extractor as well as of the specific image content (as exemplified by the two different feature descriptors and the various image collections, respectively). Although the differences can be small, the results clearly indicate that certain colour-to-greyscale conversion algorithms in an SfMworkflow constantly perform better than others. Overall, one of the best performing decolourization algorithms turns out to be a newly developed one.

The dimensions of façades and window openings in buildings are usually determined by direct measurements using tapes and plummets. In this paper, we present a semi-automated application that makes it possible to obtain building measurements by means of an indirect method based on close-range photogrammetry. This application is intended to be used with a single planar-surface measuring system that permits measurements to be made without contact with the building. This system combines the output from a digital off-the-shelf camera and a laser distance meter. These data are used within our application for image orientation and scaling. Next, the software permits calculation of the dimensions of elements on the planar façade and also provides an estimate for the precision of those dimensions. This indirect approach avoids time-consuming and risky procedures in building measurement and permits the user to take inventory of a building under construction.

From the test field Zonguldak different high and very high resolution optical satellite images are available like TK350, ASTER, KOMPSAT-1, IRS-1C, SPOT 5, KVR1000, IKONOS and QuickBird. The images partially have been achieved as close to original images (level 1A) and partially projected to a plane with constant object height (level 1B). For some images, based on direct sensor information, a good image orientation is given which for some only has to be improved by a shift in X and Y, while for others only rough orientations are distributed. In addition sometimes the orientation has to be improved by additional parameters to compensate systematic geometric effects. Some orientation information of IKONOS-and QuickBird-images is available also as rational polynomial coefficients (RPCs), describing the relation between the image and the object coordinates by a ration of polynomials. The different orientation procedures are described with their advantages and disadvantages. In most cases sub-pixel accuracy was possible. The orientation of some images could be made with different procedures leading to similar results for a sufficient number of well distributed control points. But with a smaller number and also not well distributed control points quite different results have been achieved leading to the clear result that a correct mathematical model, using the available information of the image orientation should be used. This can be done with a geometric reconstruction of the image geometry or sensor oriented rational polynomial coefficients (RPCs) while for the 3D-affinity transformation more and well distributed control points are required. The DLT-method and the terrain dependent RPCs should not be used.

With the development in space technology, new remote sensing satellites are launched around the world tremendously. The high resolution camera gives high resolution satellite images and the large data is produced by remote sensors persistently. Because of high efficiency, the vast inclusion of data with not being restricted by the spatial parameter, satellite representation winds up one of the imperative way to obtain geospatial data. With this data, the obtaining of land control points is essential in the image registration and geometric improvement of satellite pictures. In this research work, the influence of the quantity and geographical distribution of land ground control point in image registration and accurateness is examine through Voronoi Diagram (Thiessen polygon). A simulation investigation was carried out using remote sensing pictures to analyze the impact of distributed patterns of land control points on image registration and correction. The corrected values are measured by square root mean error (SRME) and with residual separations. It exhibits that the center distribution gives the most reduced SRME. Additionally, demonstrates that the land control point distribution in the center of image is less distorted in comparison to land control points positioned at borders and corners. Subsequently, the centralized uniform distribution of ground control points shows better results taking into consideration the overall deformation rate on the complete image registration.

With the development in space technology, new remote sensing satellites are launched around the world tremendously. The high resolution camera gives high resolution satellite images and the large data is produced by remote sensors persistently. Because of high efficiency, the vast inclusion of data with not being restricted by the spatial parameter, satellite representation winds up one of the imperative way to obtain geo-spatial data. With this data, the obtaining of land control points is essential in the image registration and geometric improvement of satellite pictures. In this research work, the influence of the quantity and geographical distribution of land ground control point in image registration and accurateness is examine through Voronoi Diagram (Thiessen polygon). A simulation investigation was carried out using remote sensing pictures to analyze the impact of distributed patterns of land control points on image registration and correction. The corrected values are measu...

We have examined whether blood volume changes induced by neural activation are controlled precisely enough for us to visualize the submillimeter-scale functional structure in anesthetized and awake cat visual cortex. To activate the submillimeter-scale functional structures such as iso-orientation domains in the cortex, visual stimuli (gratings) were presented to the cats. Two methods were used to examine the spatial precision of blood volume changes including changes in total hemoglobin content and changes in plasma volume: (i) intrinsic signal imaging at the wavelength of hemoglobin's isosbestic point (569 nm) and (ii) imaging of absorption changes of an intravenously injected dye. Both measurements showed that the visual stimuli elicited stimulus-nonspecific and stimulus-specific blood volume changes in the cortex. The former was not spatially localized, while the latter was confined to iso-orientation domains. From the measurement of spatial separation of the iso-orientation domains, we estimated the spatial resolution of stimulus-specific blood volume changes to be as high as 0.6 mm. The changes in stimulus-nonspecific and-specific blood volume were not linearly correlated. These results suggest the existence of fine blood volume control mechanisms in the capillary bed in addition to global control mechanisms in arteries.

between plans prescribed to points A and H was small averaged over all 3D volumes (4.9cGy). When data are recalculated including the 4 patients with implant geometry deviating from ideal, point H still receives 6Gy at 1.5-2cm, 5Gy at 2.5cm, and 4Gy at 3cm. However, D90 is reduced by an average of 34.1cGy when prescribing to point A. Conclusions: These data provide a quantitative evaluation of the correlation between point A/point H doses and volumetric dose parameters for HDR FSD implants when performing CT-based planning. When the implant approximates ideal geometry, prescribing to point A or H will ensure that 90% of volumes with radii 2cm or smaller are covered by the prescription isodose line. Prescribing to point H is more robust to implant geometries that deviate from the ideal, ensuring high D90 coverage. These results are based on a volumetric expansion of the applicator without considering OAR or target geometry. Therefore, they are only to be used as a guideline while planning, not a patient-specific assessment of the volumetric dose coverage of the plan.

The current study examines self-confidence, perceived quality, extrinsic attributes and perceived risk as drivers and inhibitors of Generation Y's purchase intentions of prototypical and me-too brands. A survey of 348 respondents demonstrated that self-confidence and perceived quality produced significant positive effects on purchase intentions for the me-too brands. Extrinsic attributes produced a significant positive effect on purchase intentions for the prototypical brand. Perceived financial/performance risk produced a significant negative effect on purchase intentions for both the prototypical and me-too brands, while perceived psychological risk produced a significant negative effect on purchase intentions for the prototypical brand. Understanding the factors underlying Gen Y's consumer behaviour is crucial, particularly due to their considerable consumption potential and the increasing sophistication of brand marketing in the marketplace.

Automatic determination of 3D information from digital images is a fundamental problem in digital photogrammetry and computer vision. The most difficult task in the problem is finding conjugate points in images. Despite the wealth information contained in stereo images, factors such as occlusions and discontinuities challenge several algorithms implemented to match conjugate points. On the other hand, multi-image matching has gained considerable attention recently since it accounts for changes in illumination conditions, camera positions, and surrounding features. Currently, a wide variety of techniques have been developed for multi-image matching. However, most of these techniques are based on one of two approaches: grouping outputs from stereo matching or looking for corresponding points in all views. The first approach results in scenarios where several false matches could be grouped. The second approach is limited to cases where points appear in all views with comparable intensity values. This paper introduces an alternative algorithm to match image points across several views. Our approach is based on locating all sets of corresponding points in all image triplets using neural networks then grouping those triplet sets that represent the same ground point. Radiometric and geometric properties are fed into a feedforward neural network designed to detect valid matches from invalid ones in all image triplets simultaneously. The detection rate of the neural network is more than 98 % and the false alarm rate is less than 2 %. Triplet matching sets are then combined if they share the same image point and their image rays have a valid intersection as measured through the colinearity equation. In order to assess the geometrical accuracy of the 3D points, the image coordinates are manually measured in the original images and object coordinates are computed and found comparable to those computed through the proposed algorithm.

ABSTRACT: The physical and generalized sensor models are two widely used imaging geometry models in the photogrammetry and remote sensing. Utilizing the rational function model (RFM) to replace physical sensor models in photogrammetric mapping is becoming a standard way for economical and fast mapping from high-resolution images. The RFM is accepted for imagery exploitation since high accuracies have been achieved in all stages of the photogrammetric process just as performed by rigorous sensor models. Thus it is likely ...

During operation of present fusion devices, the Plasma Facing Components (PFCs) are exposed to high heat fluxes. Understanding and preventing overheating of these components during long pulse discharges is a crucial safety issue for future devices like ITER. Infrared digital cameras interfaced with complex optical systems have become a routine diagnostic to measure surface temperatures in many magnetic fusion devices. Due to the complexity of the observed scenes and the large amount of data produced, the use of high computational performance hardware for real-time image processing is then mandatory to avoid PFC damages. At Tore Supra, we have recently made a major upgrade of our real-time infrared image acquisition and processing board by the use of a new Field Programmable Gate Array (FPGA) optimized for image processing. This paper describes the new possibilities offered by this board in terms of image calibration and image interpretation (abnormal thermal events detection) compared to the previous system.

We present a method to reconstruct the 3D trajectory of an airborne robotic system only from videos recorded with cameras that are unsynchronized, may feature rolling shutter distortion, and whose viewpoints are unknown. Our approach enables robust and accurate outside-in tracking of dynamically flying targets, with cheap and easy-to-deploy equipment. We show that, in spite of the weakly constrained setting, recent developments in computer vision make it possible to reconstruct trajectories in 3D from unsynchronized, uncalibrated networks of consumer cameras, and validate the proposed method in a realistic field experiment. We make our code available along with the data, including cm-accurate groundtruth from differential GNSS navigation.

This paper deals with the retrieval of vanishing points in uncalibrated images. Many authors did work on that subject in the computer vision field because the vanishing point represents a major information. In our case, starting with this information gives the orientation of the images at the time of the acquisition or the classification of the different directions of parallel lines from an unique view. The goal of this paper is to propose a simple and robust geometry embedded into a larger frame of image work starting with an efficient vanishing point extraction without any prior information about the scene and any knowledge of intrinsic parameters of the optics used.After this fully automatic classification of all segments belonging to the same vanishing point, the error analysis of the vanishing points found gives the covariance matrix on the vanishing point and on the orientation angles of the camera, when using the fact that the 3D directions of lines corresponding to the vanishing points are horizontal or vertical. A validation of estimated parameters with the help of the photo-theodolite has been experimented that demonstrate the interest of the method for real case. The algorithm has been tested on the database of a set of 100 images available on line.

Admired and despised, created and destroyed, legal and illegal: Contemporary graffiti are polarising, and not everybody agrees to label them as cultural heritage. However, if one is among the steadily increasing number of heritage professionals and academics that value these short-lived creations, their digital documentation can be considered a part of our legacy to future generations. To document the geometric and spectral properties of a graffito, digital photographs seem to be appropriate. This also holds true when documenting an entire graffiti-scape consisting of 1000s of individual creations. However, proper photo-based digital documentation of such an entire scene comes with logistical and technical challenges, certainly if the documentation is considered the basis for further analysis of the heritage assets. One main technical challenge relates to the photographs themselves. Conventional photographs suffer from multiple image distortions and usually lack a uniform scale, whi...

In this work we propose two brain extraction methods (BEM) that solely depend on the brain anatomy and its intensity characteristics. Our methods are simple, unsupervised and knowledge based. Using an adaptive intensity thresholding method on the magnetic resonance images of head scans, a binary image is obtained. The binary image is labeled using the anatomical facts that the scalp is the boundary between head and background, and the skull is the boundary separating brain and scalp. A run length scheme is applied on the labeled image to get a rough brain mask. Morphological operations are then performed to obtain the fine brain on the assumption that brain is the largest connected component (LCC). But the LCC concept failed to work on some slices where brain is composed of more than one connected component. To solve this problem a 3-D approach is introduced in the BEM. Experimental results on 61 sets of T1 scans taken from MRI scan center and neuroimage web services showed that our methods give better results than the popular methods, FSL's Brain Extraction Tool (BET), BrainSuite's Brain Surface Extractor (BSE) gives results comparable to that of Model-based Level Sets (MLS) and works well even where MLS failed. The average Dice similarity index computed using the ''Gold standard'' and the specificity values are 0.938 and 0.992, respectively, which are higher than that for BET, BSE and MLS. The average processing time by one of our methods is E1 s/slice, which is smaller than for MLS, which is E4 s/slice. One of our methods produces the lowest false positive rate of 0.075, which is smaller than that for BSE, BET and MLS. It is independent of imaging orientation and works well for slices with abnormal features like tumor and lesion in which the existing methods fail in certain cases.

An image matching algorithm is presented in this paper. A set of interest points known as SIFT features are computed for a pair of images. Every keypoint has a descriptor based on histogram of magnitude and direction of gradients. These descriptors are the primary input for the image correspondence algorithm. Initial probabilities are assigned for categories (probable matches) considering a feature point assignment to one of the category as a classification problem. Baye’s theorem is used for assigning initial probabilities. For selecting the neighbours for the left keypoint, a fixed number of pixels around the keypoint, considered as a window, are selected. The neighbours of the right keypoint are based on inspection of pair of images and the disparity range. The probabilistic estimates are iteratively improved by a relaxation labeling technique. The neighbour keypoints which will contribute to improve the probability is based on consistency property. The algorithm is effective for...

The 3D reconstruction is an essential photogrammetric application using the image geometry models. As the rational function model (RFM) has been adopted as the replacement sensor model by vendors of high-resolution satellite images (HRSIs), two methods for 3D reconstruction using the forward form of the RFM have been proposed and evaluated, including the weighted least squares adjustment and the straight line algorithm. In this research, we compared these two 3D reconstruction algorithms using Ikonos stereo ...

The application of religious symbolism is important in the evolution of medical consumption. Chinese religious belief integrates concepts of Buddhism, Daoism, and Confucianism. People personify god and goddess' characters in religious stories which influence our ideal personality in reality. According to the Match-up Hypothesis in medical product advertising, female role portrayal in patriarchal society involves the blending of beautification ritual, utilizing the marketed product, with idealized female beauty into a package intended to provide the best possible match with the prevailing ideal. Due to the influence of traditional sex stereotypes in eastern or western societies, such female portrayals provide culturally reasonable advertisements of the value of products being displayed for visualization consumption. This ideology is part of the moral fabric of society and reveals a possible social collective consciousness. The authors adopt five dimensions of religious involvement (DRI-Ideology, Ritualistic, Experiential, Consequential, and Intellectual) to explain a process of portrayals visualization and discuss the template image orientation for presenting product information in the marketplace. This study proposes the female role visualization consumption (FRVC) model to identify different elements of female role evolution stemming from religious ideology.

High-resolution satellite images, including KOMPSAT, WorldView-3, and Pléiades, are widely used for mapping and environmental monitoring. In particular, satellite images with high spatial resolution have accurate location information and provide essential spatial information. Most high-resolution satellite image files are provided with rational polynomial coefficients (RPCs) that can be used for sensor modeling. However, the RPCs have an initial bias. Therefore, most satellite image platforms and researchers match satellite images to ground control point (GCP) information and perform RPCs bias compensation of images using the matching information. In Korea, an image-based GCP chip database built using orthographic images has been provided for the georegistration of various satellite images. In this manuscript, RPCs bias compensation of KOMPSAT-3A satellite images was performed using the GCP chips, and then, the possibility of automation of RPCs bias compensation through GCP chips was analyzed. Image matching, such as area-based and edge-based techniques, was used, and the results of RPCs bias compensation using the GCP chips were analyzed through experiments for various regions. The automated compensation in both area-based or edge-based matching performed well, achieving accuracy within 1.5 pixels for test areas with various topographic features. However, the forest area posed a challenge, requiring new GCP chips with rich feature information. In addition, edge-based matching showed potentials to overcome large seasonal differences, including snow cover.

The dimensions of façades and window openings in buildings are usually determined by direct measurements using tapes and plummets. In this paper, we present a semi-automated application that makes it possible to obtain building measurements by means of an indirect method based on close-range photogrammetry. This application is intended to be used with a single planar-surface measuring system that permits measurements to be made without contact with the building. This system combines the output from a digital off-the-shelf camera and a laser distance meter. These data are used within our application for image orientation and scaling. Next, the software permits calculation of the dimensions of elements on the planar façade and also provides an estimate for the precision of those dimensions. This indirect approach avoids time-consuming and risky procedures in building measurement and permits the user to take inventory of a building under construction.

Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on both the luminance (structural) and chrominance (color) low-level content features. The statistical learning support vector machines (SVMs) are used in our approach as the classifiers. The different sources of the extracted image features, as well as the binary classification nature of SVM, require our system to be able to integrate the outputs from multiple classifiers. Both static combiner (averaging) and trainable combiner (also based on SVMs) are proposed and evaluated in this work. Furthermore, two rejection options (regular and re-enforced ambiguity rejections) are employed to improve orientation detection accuracy by sieving out images with low confidence values during the classification. Large amounts of experiments have been conducted on a database of more than 14,000 images to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper.

Direct georeferencing is a new method in photogrammetry, especially in the digital camera era. Theoretically, this method does not require ground control points (GCP) and the Aerial Triangulation (AT), to process aerial photography into ground coordinates. Compared with the old method, this method has three main advantages: faster data processing, simple workflow and less expensive project, at the same accuracy. Direct georeferencing using two devices, GPS and IMU. GPS recording the camera coordinates (X, Y, Z), and IMU recording the camera orientation (omega, phi, kappa). Both parameters merged into Exterior Orientation (EO) parameter. This parameters required for next steps in the photogrammetric projects, such as stereocompilation, DSM generation, orthorectification and mosaic. Accuracy of this method was tested on topographic map project in Medan, Indonesia. Large-format digital camera Ultracam X from Vexcel is used, while the GPS / IMU is IGI AeroControl. 19 Independent Check Point (ICP) were used to determine the accuracy. Horizontal accuracy is 0.356 meters and vertical accuracy is 0.483 meters. Data with this accuracy can be used for 1:2.500 map scale project.

Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on both the luminance (structural) and chrominance (color) low-level content features. The statistical learning support vector machines (SVMs) are used in our approach as the classifiers. The different sources of the extracted image features, as well as the binary classification nature of SVM, require our system to be able to integrate the outputs from multiple classifiers. Both static combiner (averaging) and trainable combiner (also based on SVMs) are proposed and evaluated in this work. Furthermore, two rejection options (regular and re-enforced ambiguity rejections) are employed to improve orientation detection accuracy by sieving out images with low confidence values during the classification. Large amounts of experiments have been conducted on a database of more than 14,000 images to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper.

Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on both the luminance (structural) and chrominance (color) low-level content features. The statistical learning support vector machines (SVMs) are used in our approach as the classifiers. The different sources of the extracted image features, as well as the binary classification nature of SVM, require our system to be able to integrate the outputs from multiple classifiers. Both static combiner (averaging) and trainable combiner (also based on SVMs) are proposed and evaluated in this work. Furthermore, two rejection options (regular and re-enforced ambiguity rejections) are employed to improve orientation detection accuracy by sieving out images with low confidence values during the classification. Large amounts of experiments have been conducted on a database of more than 14,000 images to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper.

It is presently expected that the stringent need for ground control for the adjustment of aerial triangulation blocks may be substantially alleviated by continous provision of in-flight gathered GPS data processed off-line in kinematic-differential mode (KDGPS). Although true in principle, this combined method cannot be considered operational as yet on the sub-decimeter accuracy level for large scale aerial photography. The paper attempts to demonstrate some of the pitfalls presently still to be expected. The investigation is based on highly redundant aerial photograpy of 1:4500 scale obtained with a modern Zeiss RMK-TOP 15/23 camera interfaced to an Ashtech LD-XU GPS-receiver. Controlled by a centimeter precision test field, the block exhibits an exceptionally high degree of interconnectedness. By comparing the antenna positions between GPS and photogrammetry, problems arising from unreliable time recording and indefinite ambiguity determination were detected. Although a novel time...

The extraction of spatial data from satellite imagery requires that precise sensor models are used to orientate images. This is particularly important with images acquired by linear sensors, such as SPOT, frequently pointed with large incidence angles. Image orientation with pixel accuracy requires that accurate ground control points are used. The acquisition of ground control is especially difficult in remote areas, where satellite images are important data sources for the production and updating of topographic maps. This paper describes a method for the orientation of SPOT panchromatic images making use of tie points with a SAR image. SAR and SPOT images compose stereo-pairs with a good stereo intersection, from which heights can be derived. For the SAR-SPOT tie-points, approximate heights are derived from parallaxes and can be corrected using altimetric ground control points. The method described makes use of the fact that the SAR image orientation can be derived from the orbit a...

Images acquired by linear array sensors on board of satellites, such as SPOT, are oriented, for mapping purposes, by rigorous sensor models. These models use a set of orbital and attitude parameters that represent the exterior orientation of an image. Rigorous values of the exterior orientation parameters are determined with ground control points (GCPs). In this article we present an alternative methodology of linear array image orientation. The sensor model is set up with approximate parameters provided with image data. The improvement of image orientation is done by applying corrections in image space. The paper justifies the conditions in which the method is applicable. Several experiments of the method were carried out with images of a mountainous region in Portugal. Initial orientation parameters, provided with images, had an accuracy of the order of 500 m. The method improved the orientation to sub-pixel accuracy, similar to the results achieved by a commercial software package that implements a rigorous sensor model.

PRISM is a three-line scanner, on board of ALOS satellite, fully dedicated to the acquisition of high resolution panchromatic stereo imagery, for the generation of global terrain elevation data. Common processes of DSM generation required accurate ground control data, which may not be available in many areas were these imagery may be more useful. This paper presents a fully automatic method for ALOS-PRISM image orientation and DSM extraction without using conventional ground control points. It is based on the extraction of a relative DSM, which is adjusted by surface matching to the SRTM-DSM. This method proved to be accurate enough for the requirements of medium map scale production, such as 1:25.000.

This paper presents a methodology to obtain an accurate exterior orientation of SPOT stereopairs using as ground control only the SRTM 3 arc second DEM. The method is based on the extraction of a relative DEM from the stereopair, after a relative orientation. This DEM is then matched to the SRTM DEM by correlation. Small portions of the extracted DEM are adjusted, leading to corrections of the geolocation of the stereopair. A set of ground control points are simulated in order to enter a standard procedure for image orientation. The method was tested with two stereopairs, from Portugal and France. The accuracy of the exterior orientation obtained is similar to what is achieved with GCPs measured in maps of scale 1:25,000. The method can be largely automated and may be useful to make a better use of many thousands of stereopairs available in the SPOT archive, although only for areas with some relief. Another application is the extraction of data to fill SRTM void pixels, especially in mountains.

In biometrics we use distinctive physical features for identification and verification of identity. The most famous technique is identification by fingerprints. This technique use unique structure created by papillary lines for unambiguous identification. Thesis contains methods which were created throughout the years for analysis and adjustments of fingerprint. The algorithm is based on compairng two pairs of minitua and calculating transform matrix for correct alignment. Algorithm is tested on dataset created from LivDet databases. Performance of algorithm is represented by value EER which is compared with EERs of other algorithms tested in FVC 2006

In this paper we present different methods for the calibration and orientation of monocular image sequences and the 3D reconstruction of human characters. Three different situations are considered: a static character imaged with a moving camera, a moving character imaged with a fix camera and a moving character imaged with a moving camera. A self-acquired sequence is used in the first case while in the other cases we used existing sequences available on the Internet or digitized from old videotapes. Most of the image-based techniques use probabilistic approaches to model a character from monocular sequences; on the other hand we use a determinist approach, recovering characterís model and movement through a camera model. The recovered human models can be used for visualization purposes, to generate new virtual scenes of the analyzed sequence or for gait analysis.

An image matching algorithm is presented in this paper. A set of interest points known as SIFT features are computed for a pair of images. Every keypoint has a descriptor based on histogram of magnitude and direction of gradients. These descriptors are the primary input for the image correspondence algorithm. Initial probabilities are assigned for categories (probable matches) considering a feature point assignment to one of the category as a classification problem. Baye’s theorem is used for assigning initial probabilities. For selecting the neighbours for the left keypoint, a fixed number of pixels around the keypoint, considered as a window, are selected. The neighbours of the right keypoint are based on inspection of pair of images and the disparity range. The probabilistic estimates are iteratively improved by a relaxation labeling technique. The neighbour keypoints which will contribute to improve the probability is based on consistency property. The algorithm is effective for...

of Ph.D thesis (accepted February, 2002) This thesis addresses the problem of 3D reconstruction from sets of images of a particular scene and the associated methodologies used to uncover the relationship among the views under consideration. The problem of 3D reconstruction is one of the extensively studied fields of computer vision. The thesis sets out with a brief introduction on the matters inspired the author to embark on this field and a description of the different applications generated as a by product to the solution of the correspondence problem. The thesis is designed to be self contained not only in its integrity but also among chapters (only a faint back and fro reference among chapters). It is my wish that each chapter stands as a prerequisite to the next one, however, readers with a knowledge of a chapter may consider to skip to the next. Any computer vision application or algorithm uses a bunch of feature point, edge and comer, detectors as a preprocessor to assist in ...

In this paper a simple architecture for an image oriented virtual machine targeted to computer vision applications is introduced. This virtual machine provides a low level approach to image processing working on very high level data structures which allows developers to setup the sequence of processing actions in an easy way. Additionally, this architecture provides a common environment for prototyping and production systems simplifying the deployment process of the final application.

We propose a new approach for tracking the cardiac motion by using simultaneously short-axis and long-axis MR images in non-rigid registration. The fusion of two image orientations allows to track more precisely the basal and apical movement of the ventricles. In addition, the motion of the atria is tracked. Correlation coefficients were 0.94 at the systolic phase and 0.97 at the diastolic phase as the volumes of manually and automatically detected chambers were compared. The results were obtained using 7 subjects.

KOMPSAT-3A (KOrea MultiPurpose SATellite-3A) was launched in March 25 2015 with specification of 0.5 meters resolution panchromatic and four 2.2 meters resolution multi spectral sensors in 12km swath width at nadir. To better understand KOMPSAT-3A positional accuracy, this paper reports a test result on the accuracy of recently released KOMPSAT-3A beta test images. A number of ground points were acquired from 1:1,000 digital topographic maps over the target area for the accuracy validation. First, the original RPCs (Rational Polynomial Coefficients) were validated without any GCPs (Ground Control Points). Then we continued the test by modeling the errors in the image space using shift-only, shift and drift, and the affine model. Ground restitution accuracy was also analyzed even though the across track image pairs do not have optimal convergence angle. The experimental results showed that the shift and drift-based RPCs correction was optimal showing comparable accuracy of less than 1.5 pixels with less GCPs compared to the affine model.

The benefit of early chemotherapy persisted a shared frailty univariate cox proportional hazards analysis following propensity score-matching (HR 0.56; 95% CI 0.41-0.77, p<0.01). No differences in OS were present between CRT, CRC, and CR (pZ0.29). Conclusion: Among elderly patients receiving adjuvant chemotherapy and radiation, those receiving early chemotherapy were associated with prolonged OS.

We present an automatic and efficient method to register and stitch thousands of video frames into a large panoramic mosaic. Our method preserves the robustness and accuracy of image stitchers that match all pairs of images while utilizing the ordering information provided by video. We reduce the cost of searching for matches between video frames by adaptively identifying key frames based on the amount of image-to-image overlap. Key frames are matched to all other key frames, but intermediate video frames are only matched to temporally neighboring key frames and intermediate frames. Image orientations can be estimated from this sparse set of matches in time quadratic to cubic in the number of key frames but only linear in the number of intermediate frames. Additionally, the matches between pairs of images are compressed by replacing measurements within small windows in the image with a single representative measurement. We show that this approach substantially reduces the time required to estimate the image orientations with minimal loss of accuracy. Finally, we demonstrate both the efficiency and quality of our results by registering several long video sequences.

In this work we propose two brain extraction methods (BEM) that solely depend on the brain anatomy and its intensity characteristics. Our methods are simple, unsupervised and knowledge based. Using an adaptive intensity thresholding method on the magnetic resonance images of head scans, a binary image is obtained. The binary image is labeled using the anatomical facts that the scalp is the boundary between head and background, and the skull is the boundary separating brain and scalp. A run length scheme is applied on the labeled image to get a rough brain mask. Morphological operations are then performed to obtain the fine brain on the assumption that brain is the largest connected component (LCC). But the LCC concept failed to work on some slices where brain is composed of more than one connected component. To solve this problem a 3-D approach is introduced in the BEM. Experimental results on 61 sets of T1 scans taken from MRI scan center and neuroimage web services showed that our methods give better results than the popular methods, FSL's Brain Extraction Tool (BET), BrainSuite's Brain Surface Extractor (BSE) gives results comparable to that of Model-based Level Sets (MLS) and works well even where MLS failed. The average Dice similarity index computed using the ''Gold standard'' and the specificity values are 0.938 and 0.992, respectively, which are higher than that for BET, BSE and MLS. The average processing time by one of our methods is E1 s/slice, which is smaller than for MLS, which is E4 s/slice. One of our methods produces the lowest false positive rate of 0.075, which is smaller than that for BSE, BET and MLS. It is independent of imaging orientation and works well for slices with abnormal features like tumor and lesion in which the existing methods fail in certain cases.

Purpose-The purpose of this paper is to review and provide a detailed performance evaluation of a number of texture descriptors that analyse texture at micro-level such as local binary patterns (LBP) and a number of standard filtering techniques that sample the texture information using either a bank of isotropic filters or Gabor filters. Design/methodology/approach-The experimental tests were conducted on standard databases where the classification results are obtained for single and multiple texture orientations. The authors also analysed the performance of standard filtering texture analysis techniques (such as those based of LM and MR8 filter banks) when applied to the classification of texture images contained in standard Outex and Brodatz databases. Findings-The most important finding resulting from this study is that although the LBP/C and the multi-channel Gabor filtering techniques approach texture analysis from a different theoretical perspective, in this paper the authors have experimentally demonstrated that they share some common properties in regard to the way they sample the macro and micro properties of the texture. Practical implications-Texture is a fundamental property of digital images and the development of robust image descriptors plays a crucial role in the process of image segmentation and scene understanding. Originality/value-This paper contrast, from a practical and theoretical standpoint, the LBP and representative multi-channel texture analysis approaches and a substantial number of experimental results were provided to evaluate their performance when applied to standard texture databases.