Papers by Josue Álvarez-Borrego
Limnetica, 2001
We propose an automatic system for diatom localization and identification with a modular structur... more We propose an automatic system for diatom localization and identification with a modular structure. The main contribution of this work is to provide a complete automatic system for the analysis of phytoplanktonic samples in brightfield microscopy. The overall procedure consists in two parts: first, frame gathering at low magnification and second, further analysis at higher magnification. At low magnification the goal is to obtain a panoramic overview of the full sample by tiling each frame. Subsequent processing steps will provide the localization and size of each particle in each frame for further analysis. The localization method based on image fusion techniques provides more robust and accurate particle detection than other methods reported in the literature. From the size information we obtain a useful cue about the objective to use. At higher magnification we developed new autofocusing techniques providing a fast and accurate focused image. Because particles present a volumetric structure, we propose the use of multifocus fusion techniques for merging in a single plane the focused parts from neighbouring the best focused image. Then we applied a particle selection analysis to reduce the number of images to analyze, i.e. to discriminate diatoms from debris. This is the most challenging step , due to large variability of shapes, diatom fragmentation, particle overpopulation and diatom hiding. The latter is not described in the present paper and will be the subject for a forthcoming publication. Finally, for diatom identification we use the scale transform technique and a cepstrum-based cross-correlation technique.
Revista de biología marina y oceanografía, 2006
Identification of platyhelminth parasites of the wild bullseye pufferfish (Sphoeroides annulatus ... more Identification of platyhelminth parasites of the wild bullseye pufferfish (Sphoeroides annulatus Jenyns, 1853) using invariant digital color correlation Identificación de parásitos platelmintos del botete silvestre (Sphoeroides annulatus Jenyns, 1853) usando una correlación invariante digital a color
Applications of Digital Image Processing XXIX, 2006
22nd Congress of the International Commission for Optics: Light for the Development of the World, 2011
A nonlinear correlation digital algorithm invariant to position, rotation and scale using a binar... more A nonlinear correlation digital algorithm invariant to position, rotation and scale using a binary mask is presented. Binary and gray images are used in order to analyze this new identification digital system. The problem images had a ± 30% of maximum scale variation with respect to the target. Some composite filters had a very good performance in this range. The rotation goes from 0 o to 359 o. From the Fourier transform, concentric binary rings masks were elaborated, using the real or the imaginary part. From the ring mask the signatures of the problem image and the target were obtained. The objective is identifying a specific target no matter the position, rotation or scale presented in the problem image. A statistical analysis was done to know the mean correlation confidence level. In this work, a new, fast and functional position, scale and rotation invariance pattern recognition digital system was obtained.
Fourier Transform - Signal Processing, 2012
ICO20: Optical Information Processing, 2006
In this paper we present an algorithm to determine the multifocus image fusion from several color... more In this paper we present an algorithm to determine the multifocus image fusion from several color microbiological images captured from the best focusing region. This focusing region is built by including several images up and down starting from Z position of the best image in focus. The captured RGB images are converted to YCbCr color space to have the color CbCr and intensity Y channels separated with the objective to preserve the color information of the best in focus image. However this algorithm utilizes the Fourier approach by using the Y channel frequency content via analyzing the Fourier coefficients for retrieving the high frequencies in order to obtain the best possible characteristics of every captured image. After this process, we construct the fused image with these coefficients and color information for the optimum in focus image in the YCbCr color space, as a result, we obtain a precise final RGB fused image.
Applications of Digital Image Processing XXVI, 2003
2010 International Conference on Biosciences, 2010
In this paper a novel technique is developed to classify White Spot Syndrome Virus (WSSV) inclusi... more In this paper a novel technique is developed to classify White Spot Syndrome Virus (WSSV) inclusion bodies found in shrimp tissues by the analysis of digitalized images from infected samples. Since the early 90's, WSSV has been affecting the economy of shrimp producers around the world restraining aquaculture production. Once the clinical signs are developed; mortality can reach 100% in 3 days. Several techniques have been implemented and developed for viral and bacterial diagnostics from penaeid shrimps; however histology is still considered the common tool in medical and veterinary diagnostics tasks. WSSV slide images were acquired by a computational image capture system and a new spectral signature index is developed to obtain a quantitative measurement of the complexity pattern found in WSSV inclusion bodies. Representative groups of WSSV inclusion bodies from infected shrimp tissues and organs were analyzed. The results show that inclusion bodies analyzed are well defined in a clear numerical fringe, obtained by the calculation by this spectral signature index.
Algorithms and Systems for Optical Information Processing IV, 2000
A new autofocus algorithm based on one-dimensional Fourier transform and Pearson correlation for ... more A new autofocus algorithm based on one-dimensional Fourier transform and Pearson correlation for Z automatized microscope is proposed. Our goal is to determine in fast response time and accuracy, the best focused plane through an algorithm. We capture in bright and dark field several images set at different Z distances from biological organism sample. The algorithm uses the one-dimensional Fourier transform to obtain the image frequency content of a vectors pattern previously defined comparing the Pearson correlation of these frequency vectors versus the reference image frequency vector, the most out of focus image, we find the best focusing. Experimental results showed the algorithm has fast response time and accuracy in getting the best focus plane from captured images. In conclusions, the algorithm can be implemented in real time systems due fast response time, accuracy and robustness. The algorithm can be used to get focused images in bright and dark field and it can be extended to include fusion techniques to construct multifocus final images beyond ofthis paper.
Revista de biología marina y oceanografía, 2006
4th Iberoamerican Meeting on Optics and 7th Latin American Meeting on Optics, Lasers, and Their Applications, 2001
The taxonomic identification of diatom species that constituted phytoplankton communities in remo... more The taxonomic identification of diatom species that constituted phytoplankton communities in remote times is determining in several research fields like ecology, evolution, paleoecology and biostratigraphy. In the last 30 years the use of fossil diatoms like environmental indicators has become of prime importance. However the use of these organisms is limited since they are found in sediment samples mostly fragmented or pulverized. This may lead to confusion and loss of information. In this work we used invariant correlation to identify 12 species of fossil diatoms. With this method we were able to identify the diatom species from only a small fragment of the organisms. This methodology can be used for the development of an automated system of plankton identification. An automatized identification of diatoms would be able to guarantee a faster identification and also would reduce the time necessary for acomplishing analysis of samples highly fragmented.
Applications of Digital Image Processing XXXI, 2008
Gayana (Concepción), 2013
Fourier Transform - Signal Processing, 2012
Fourier Transform - Signal Processing, 2012
Pattern Recognition and Image Analysis, 2007
Two effective algorithms for the removal of impulse noise from color images are proposed. The alg... more Two effective algorithms for the removal of impulse noise from color images are proposed. The algorithms consist of two steps. The first algorithm detects outliers with the help of spatial relations between the components of a color image. Next, the detected noise pixels are replaced with the output of a vector median filter over a local spatially connected area excluding the outliers, while noise-free pixels are left unaltered. The second algorithm transforms a color image to the YCbCr color space that perfectly separates the intensity and color information. Then outliers are detected using spatial relations between transformed image components. The detected noise pixels are replaced with the output of a modified vector median filter over a spatially connected area. Simulation results in test color images show a superior performance of the proposed algorithms compared with the conventional vector median filter. The comparisons are made using the mean square error, the mean absolute error, and a subjective human visual error criterion.
Optical Engineering, 2002
Cholera is an acute intestinal infectious disease. It has claimed many lives throughout history, ... more Cholera is an acute intestinal infectious disease. It has claimed many lives throughout history, and it continues to be a global health threat. Cholera is considered one of the most important emergence diseases due its relation with global climate changes. The automated methods like the optical systems represent a new trend to make more accurate measurements about the presence and quantity of this microorganism in its natural environment. The automatic systems eliminate the observer bias and reduce the analysis time. The goal of this work is evaluate the utility of coherent optical systems with invariant correlation for the recognition of Vibrio cholerae O1. Images of scenes were recorded with a CCD camera and decomposed in three RGB channels. A numeric simulation was developed to identify the bacteria in the different samples through an invariant correlation technique. There was not variation when we repeated the correlation and the variation between images correlation was minimum. The position, scale and rotation invariant recognition was made with scale transform through the Mellin transform. The algorithm to recognize Vibrio cholerae O1 was the presence of correlation peaks in green channel output and absence in red and blue channels. The discriminate criterion was the presence of correlation peaks in red, green and blue channels.
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Papers by Josue Álvarez-Borrego