Papers by Azeddine Beghdadi
2022 IEEE International Conference on Image Processing (ICIP)
In this paper, we propose a new comprehensive Video Surveillance Quality Assessment Dataset (VSQu... more In this paper, we propose a new comprehensive Video Surveillance Quality Assessment Dataset (VSQuAD) dedicated to Video Surveillance (VS) systems. In contrast to other public datasets, this one contains many more videos with distortions and diversified content from common video surveillance scenarios. These videos have been artificially degraded with various types of distortions (single distortion or multiple distortions simultaneously) at different severity levels. In order to improve the efficiency of the surveillance systems and the versatility of the video quality assessment dataset, night vision CCTV videos are also included. Furthermore, a comprehensive analysis of the content in terms of diversity and challenging problems is also presented in this study. The interest of such database is twofold. First, it will serve for benchmarking different video distortion detection and classification algorithms. Second, it will be useful for the design of learning models for various challenging VS problems such as identification and removal of the most common distortions. The complete dataset is made publicly available as part of a challenge session in this conference through the following link: https://www.l2ti.univ-paris13.fr/VSQuad/.
Time-Frequency Signal Analysis and Processing, 2016
Time-frequency (t, f) applications are now so widespread that they cannot be comprehensively cove... more Time-frequency (t, f) applications are now so widespread that they cannot be comprehensively covered in one volume. For this reason, this chapter aims to further illustrate the (t, f) approach by selecting a few key generic applications of diagnosis and monitoring. The topic is represented by seven sections covering a wide range of diverse applications. One key application is electrical power quality as it is often severely affected by transient disturbances. It is necessary to detect and assess their effect on voltage and current stability. This is achieved by a time-localized frequency analysis where the instantaneous frequency (IF) allows assessing disturbance propagation (Section 15.1). In the automotive industry, the treatment and prevention of knock is a major problem for internal combustion engines as car spark knocks caused by an abnormal combustion may lead to engine damage. The Wigner-Ville distribution is used to optimize the position for placement of knock sensors (Section 15.2). Other applications involve signals that have dispersive spectral delays governed by a power law, such as dispersive propagation of a shock wave in a steel beam and cetacean mammal whistles. A power class of TFDs suitable for such applications is formulated and a methodology is described (Section 15.3). In applications of image processing, image quality may be assessed using a 2D-WVD based measure correlated with subjective human evaluations. It is shown that this SNR measure based on the WVD outperforms conventional SNR measures (Section 15.4). Some general principles of (t, f) diagnosis are then reviewed for medical applications with focus on heart sound abnormality diagnosis (Section 15.5). For machine condition monitoring, a task crucial to the competitiveness of a wide range of industries, the tasks of detecting and diagnosing faults in machines, is made easier using (t, f) approaches such as the WVD, wavelets, and wavelet packets (Section 15.6). The last section presents a specific example of condition monitoring of assets using (t, f) methods that focus on the prevention of steel beam damage (Section 15.7).
Scientia Iranica, Sep 9, 2023
Human behavior analysis and visual anomaly detection are important applications in elds such as v... more Human behavior analysis and visual anomaly detection are important applications in elds such as video surveillance, security systems, intelligent houses, and elderly care. People re-identi cation is one of the main steps in a surveillance system that directly a ects system performance; and variations in appearance, pose, and scene illumination may be challenging issues for such a system. Previous re-identi cation approaches faced limitations while considering appearance changes in their tracking task. This paper proposes a new approach for people's re-identi cation using a descriptor that is robust to appearance changes. In our proposed method, the enhanced Gaussian Of Gaussian (GOG) and the Hierarchical Gaussian Descriptors (HGDs) are employed to extract feature vectors from images. Experimental results on a number of commonly used people re-identi cation databases imply the superiority of the proposed approach in people re-identi cation compared to other existing approaches.
IEEE Conference Proceedings, 2016
Biomedical Engineering Online, Oct 19, 2018
IEEE Conference Proceedings, 2020
HAL (Le Centre pour la Communication Scientifique Directe), 2009
International audienc
arXiv (Cornell University), Jul 13, 2019
The recent advances in 3D acquisition and display technologies have led to the use of stereoscopy... more The recent advances in 3D acquisition and display technologies have led to the use of stereoscopy for a wide range of applications. The quality assessment of such stereo data becomes of great interest especially when the reference image is not available. For this reason, we propose in this paper a no-reference 3D image quality assessment algorithm based on joint statistical modeling of the wavelet subband coefficients of the stereo pairs. More precisely, we resort to bivariate and multivariate statistical modeling of the texture images to build efficient statistical features. These features are then combined with the depth ones and used to predict the quality score based on machine learning tools. The proposed methods are evaluated on LIVE 3D database and the obtained results show the good performance of joint statistical modeling based approaches.
Electronics Letters, Oct 1, 2016
This Letter introduces a novel framework for blind blur assessment in colour images using higher ... more This Letter introduces a novel framework for blind blur assessment in colour images using higher order singular values. The RGB colour image is seen as a third-order tensor to exploit the spatial and inter-channel correlations, so that blurring effects are captured more robustly. The tensor is decomposed into different two-dimensional matrices, also called unfoldings. The conventional singular value decomposition is carried out for these unfoldings instead of computing it for the luminance component alone. The experiments were performed on several publicly available databases and the results validate the superiority of the proposed metric among different state-of-the-art blind blur assessment metrics. The proposed framework for image quality assessment (IQA) from colour images fits well with the current trends and research efforts put in enhancing the quality of experience for different multimedia applications and in benchmarking new imaging and sensing technologies including camera and other vision systems with IQA capabilities.
Computer Methods and Programs in Biomedicine, Jun 1, 2017
Background and Objective: For more than a decade, computer-assisted surgical systems have been he... more Background and Objective: For more than a decade, computer-assisted surgical systems have been helping surgeons to plan liver resections. The most widespread strategies to plan liver resections are: drawing traces in individual 2D slices, and using a 3D deformable plane. In this work, we propose a novel method which requires low level of user interaction while keeping high flexibility to specify resections. Methods: Our method is based on the use of Bézier surfaces, which can be deformed using a grid of control points, and distance maps as a base to compute and visualize resection margins (indicators of safety) in realtime. Projection of resections in 2D slices, as well as computation of resection volume statistics are also detailed. Results: The method was evaluated and compared with state-of-the-art methods by a group of surgeons (n = 5 , 5-31 years of experience). Our results show that theproposed method presents planning times as low as state-of-the-art methods (174 s median time) with high reproducibility of results in terms of resected volume. In addition, our method not only leads to smooth virtual resections easier to perform surgically compared to other state-of-the-art methods, but also shows superior preservation of resection margins. Conclusions: Our method provides clinicians with a robust and easy-to-use method for planning liver resections with high reproducibility, smoothness of resection and preservation of resection margin. Our results indicate the ability of the method to represent any type of resection and being integrated in real clinical work-flows.
Signal Processing-image Communication, May 1, 2017
Since a large proportion of the information that is received daily is in the form images, a highl... more Since a large proportion of the information that is received daily is in the form images, a highly effective no-reference stereo image quality assessment (SIQA) method is desired. This paper proposes an improved method that covers wide qualityaware features, including the structure, color, luminance, phase and human visual system (HVS). To be specific, since human eyes are highly sensitive to the structure of images, the gradient magnitude (GM) and gradient orientation (GO) are extracted from left and right views of the stereo image. Considering the influence of color distortions, the images are decomposed into the RGB channels to be processed, and the local gradient of the color image is obtained by adding up the RGB gradient vectors. In addition, according to the study of the two main visual channels, especially the cyclopean and disparity maps, the binocular related images of position and phase congruency are generated. Correspondingly, two special dictionaries for the gradient and phase are trained to parse the high dimensional sample sets. The experimental results show that the proposed metric always achieves high consistency with human subjective assessments for both symmetric and asymmetric distortions.
Research Square (Research Square), Sep 16, 2022
In this paper, a computer-aided method is proposed for abnormality detection Wireless Capsule End... more In this paper, a computer-aided method is proposed for abnormality detection Wireless Capsule Endoscopy (WCE) video frames. Common abnormalities in WCE images include ulcers, bleeding, Angiodysplasia, Lymphoid Hyperplasia, and polyp. In this paper, deep features and Hand-crafted features are combined to detect these abnormalities in WCE images. There are no sufficient images to train deep structures therefore the ResNet50 pertained model is used to extract deep features. Hand-crafted features are associated with color, shape, and texture. They are extracted from the region of interest (ROI), i.e. suspicious region. The expectation Maximization (EM) algorithm is used to extract more distinct areas in the background as ROI. The expectation Maximization (EM) algorithm is configured in a way that can extract the area with a distinct texture and color as ROI. The EM algorithm is also initialized with a new fast method which leads to an increase in the accuracy of the method. We also used a novel idea to reveal unexpected color changes in the background due to existing lesions as a feature set. A large number of features are created by the method, so the minimum redundancy maximum relevance approach is used to select a subset of more effective features. These selected features are then fed to a Support Vector Machine for classification. The results show that the proposed approach can detect mentioned abnormalities in WCE frames with the accuracy of 97.82%
arXiv (Cornell University), Dec 27, 2018
People counting in sports venues is emerging as a new domain in the field of video surveillance. ... more People counting in sports venues is emerging as a new domain in the field of video surveillance. People counting in these venues faces many key challenges, such as severe occlusions, few pixels per head, and significant variations in person's head sizes due to wide sport areas. We propose a deep model based method, which works as a head detector and takes into consideration the scale variations of heads in videos. Our method is based on the notion that head is the most visible part in the sports venues where large number of people are gathered. To cope with the problem of different scales, we generate scale aware head proposals based on scale map. Scale aware proposals are then fed to the Convolutional Neural Network (CNN) and it provides a response matrix containing the presence probabilities of people observed across scene scales. We then use non-maximal suppression to get the accurate head positions. For the performance evaluation, we carry out extensive experiments on two standard datasets and compare the results with state-of-the-art (SoA) methods. The results in terms of Average Precision (AvP), Average Recall (AvR), and Average F1-Score (AvF-Score) show that our method is better than SoA methods.
Journal of Healthcare Engineering, Oct 18, 2021
Image guided surgery systems aim to provide navigation to surgeons in order to improve accuracy a... more Image guided surgery systems aim to provide navigation to surgeons in order to improve accuracy and safety of the procedures. Through stereo reconstruction algorithms, it is possible to generate 3D surfaces intra-operatively by means of a laparoscopic stereo-camera. This study aims to setup a simulation system and quantitatively validate a recent proposed reconstruction algorithm with application to laparoscopic liver resection surgery. The intra-operative surface will be used to guide model to patient registration. This will also improve accuracy of the navigation by correcting intra-operative deformations of the liver, such as those due to pneumoperitoneum. The accuracy results of the reconstruction method was found to be $3.7\pm 0.8$ mm in terms of Hausdorff distance. The validation therefore indicates the feasibility and accuracy of the surface reconstruction method.
The CEED2016 is newly developed image database dedicated for contrast enhancement evaluation. The... more The CEED2016 is newly developed image database dedicated for contrast enhancement evaluation. The database contains 30 original color images and 180 enhanced images obtained using six different CE methods. The database is built with our own captured images and some common pictures used by the image processing community. The subjective experiments were performed at Universite Paris 13 at Laboratoire de Traitement et Transport de l'Information (L2TI). The images were displayed on a calibrated LCD monitor in a dark room environment to avoid any problem with the illumination adaptation of background. Twenty-three observers, 10 experts, and 13 non-experts, from different age groups, gender, and background participated in the experiments. To obtain the ranking scores, we adopted a balanced pairwise preference based ranking protocol. The interface for the subjective experiments was developed in Matlab, where, for each original image, we randomly displayed all possible pair combinations of enhanced images to the observers. We also showed the original image in the center of the screen (a pair of enhanced images are to its left and right), to facilitate the analysis of after effects of CE. The observers had the choice to rank equally similar stimuli. In the PC ranking protocol, each enhanced image is compared with the others in pairs and ranking results are stored in a preference matrix.
In this paper, a computer-aided method is proposed for abnormality detection Wireless Capsule End... more In this paper, a computer-aided method is proposed for abnormality detection Wireless Capsule Endoscopy (WCE) video frames. Common abnormalities in WCE images include ulcers, bleeding, Angiodysplasia, Lymphoid Hyperplasia, and polyp. In this paper, deep features and Hand-crafted features are combined to detect these abnormalities in WCE images. There are no sufficient images to train deep structures therefore the ResNet50 pertained model is used to extract deep features. Hand-crafted features are associated with color, shape, and texture. They are extracted from the region of interest (ROI), i.e. suspicious region. The expectation Maximization (EM) algorithm is used to extract more distinct areas in the background as ROI. The expectation Maximization (EM) algorithm is configured in a way that can extract the area with a distinct texture and color as ROI. The EM algorithm is also initialized with a new fast method which leads to an increase in the accuracy of the method. We also used...
IS&T International Symposium on Electronic Imaging Science and Technology, Feb 14, 2016
Endoscopic image enhancement has become a very popular research field due to the success of minim... more Endoscopic image enhancement has become a very popular research field due to the success of minimally invasive interventions and the innovation of new technological treatment and diagnosis tools such as stereoscopic laparoscopes and the wireless capsule endoscopy. In spite of the important advances achieved in terms of image processing and enhancement, only a few techniques can be adapted to stereo endoscopic images. This can be explained by the specificities of the stereo endoscopic video acquisition process, the surgical tasks artifacts and the endoscopic domain characteristics (e.g., organ textures,edges, color distribution). In this paper we present a contrast enhancement method for stereo endoscopic images taking into consideration some of these specificities, namely those of the acquired stereo images i.e. the depth information, the binocular vision and the organs boundaries/textures. The idea is to enhance the image quality by a contrast enhancement process that exploits the local image activity, the depth information and the binocular just noticeable difference (BJND) model. The results of the conducted subjective experiment show that the proposed method produces stereo endoscopic images with sharper details of the underlying tissues and organs, without introducing any halo effect or overshooting. The observers reported as well a more depth feeling and less visual fatigue when perceiving the enhanced stereo endoscopic images.
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Papers by Azeddine Beghdadi