Edgardo Felipe - Academia.edu (original) (raw)

Papers by Edgardo Felipe

Research paper thumbnail of Optimal Scheduling for the Performance Optimization of SpMV Computation using Machine Learning Techniques

Research paper thumbnail of Robust image registration for analysis of multisource eye fundus images

Journal of intelligent & fuzzy systems, Mar 23, 2024

Research paper thumbnail of Images retrieval using wavelets, histograms and sub images

Research on Computing Science, 2004

Research paper thumbnail of An adaptive color similarity function suitable for image segmentation and its numerical evaluation

Color Research and Application, May 20, 2016

Research paper thumbnail of Leukocytes Detection, Classification and Counting in Smears of Peripheral Blood

Revista mexicana de ingeniería biomédica, 2014

Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniqu... more Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniques of digital image processing, we developed a computational system platform-independent, which is able to identify, to classify and to count five normal types of leukocytes: neutrophils, eosinophils, basophils, monocytes and lymphocytes. It is important to emphasize that this work does not attempt to differentiate between smears of leukocytes coming from healthy and sick people; this is because most diseases produce a change in the differential count of leukocytes rather than in theirs forms. In the other side, the system could be used in emerging areas such as the topographic hematology and the chronobiology. Automatic classifier of leukocytes, k-NN, Minkowski metric, Pattern recognition, Digital image processing.

Research paper thumbnail of Leukocytes Detection, Classification and Counting in Smears of Peripheral Blood

Revista mexicana de ingeniería biomédica, 2014

Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniqu... more Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniques of digital image processing, we developed a computational system platform-independent, which is able to identify, to classify and to count five normal types of leukocytes: neutrophils, eosinophils, basophils, monocytes and lymphocytes. It is important to emphasize that this work does not attempt to differentiate between smears of leukocytes coming from healthy and sick people; this is because most diseases produce a change in the differential count of leukocytes rather than in theirs forms. In the other side, the system could be used in emerging areas such as the topographic hematology and the chronobiology. Automatic classifier of leukocytes, k-NN, Minkowski metric, Pattern recognition, Digital image processing.

Research paper thumbnail of Image Retrieval Based on Wavelet Transform and Neural Network Classification

Computación Y Sistemas, Dec 31, 2007

The problem of retrieving images from a database is considered. In particular, we retrieve images... more The problem of retrieving images from a database is considered. In particular, we retrieve images belonging to one of the following six categories: 1) commercial planes in land, 2) commercial planes in air, 3) war planes in land, 4) war planes in air, 5) small aircraft in land, and 6) small aircraft in the air. During training, a wavelet-based description of each image is first calculated using Daubechies 4-wavelet transformation. The resulting coefficients are used to train a neural network (NN). During classification, test images are treated by the already trained NN. Three different ways to obtain the coefficients of the Daubechies transform were proposed and tested: from the entire image color channels, from the histogram of the biggest circular window inside the image color channels, and from the histograms of the square sub-images in the image color channels of the original image. 120 images were used for training and 240 for testing. The best efficiency of 88% was obtained with the third method.

Research paper thumbnail of Reconocimiento de rostros mediante estructuras faciales antropométricas

Research in Computing Science, Dec 31, 2018

Resumen. Las estructuras faciales antropométricas son estructuras que se obtienen mediante puntos... more Resumen. Las estructuras faciales antropométricas son estructuras que se obtienen mediante puntos somatométricos (los cuales son empleados para la extracción de características craneofaciales). En este trabajo se propone una estructura facial antropométrica que contribuya al desarrollo de un método que realice reconocimiento de rostros de manera automática. Este método está basado principalmente en cinco etapas: extracción de coordenadas de los puntos somatométricos, creación de la estructura antropométrica, cálculo de distancias entre puntos, detección deángulos de los puntos y cálculo de proporciones respecto a las distancias. Las distancias y losángulos se obtienen con base en la relación de los puntos, relación que es establecida con la estructura antropométrica propuesta. A diferencia de otros trabajos relacionados con el reconocimiento de rostros, el método propuesto utiliza solamente nueve puntos, lo que es, hasta ahora, uno de los menores números de puntos utilizados.

Research paper thumbnail of Influence of Luminance L* in the L*a*b* Color Space during Color Segmentation in Highly Saturated Color Images

Research in Computing Science, Dec 31, 2015

In this paper a study of the influence of luminance L* at the CIE L* a* b* color space during col... more In this paper a study of the influence of luminance L* at the CIE L* a* b* color space during color segmentation in highly saturated color images is presented. A comparative study is made between the behavior of segmentation in color images using (1) the Euclidean metric of the RGB channels (2) the Euclidean metric of a* and b* in CIE L*a*b* color space and (3) an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation, synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results it was obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume. In the majority of cases the CIE L*a*b color space was more influenced by the faded shadow than the RGB color space. The segmentation using the Euclidean metric in L*a*b* color space suffered errors in all cases. It manifested in different degrees and at different levels of faded shadow (less than 10% to 80%).

Research paper thumbnail of An Adaptive Color Similarity Function for Color Image Segmentation

Lecture Notes in Computer Science, 2011

In this paper an interactive, semiautomatic image segmentation method is presented which, process... more In this paper an interactive, semiautomatic image segmentation method is presented which, processes the color information of each pixel as a unit, thus avoiding color information scattering. The process has only two steps: 1) The manual selection of few sample pixels of the color to be segmented in the image; and 2) The automatic generation of the so called Color Similarity Image (CSI), which is just a gray level image with all the tonalities of the selected colors. The color information of every pixel is integrated in the segmented image by an adaptive color similarity function designed for direct color comparisons. The color integrating technique is direct, simple, and computationally inexpensive and it has also good performance in gray level and low contrast images.

Research paper thumbnail of Image Filter Based on Block Matching, Discrete Cosine Transform and Principal Component Analysis

Lecture Notes in Computer Science, 2017

An algorithm for filtering the images contaminated by additive white Gaussian noise is proposed. ... more An algorithm for filtering the images contaminated by additive white Gaussian noise is proposed. The algorithm uses the groups of Hadamard transformed patches of discrete cosine coefficients to reject noisy components according to Wiener filtering approach. The groups of patches are found by the proposed block similarity search algorithm of reduced complexity performed on block patches in transform domain. When the noise variance is small, the proposed filter uses an additional stage based on principal component analysis; otherwise the experimental Wiener filtering is performed. The obtained filtering results are compared to the state of the art filters in terms of peak signal-to-noise ratio and structure similarity index. It is shown that the proposed algorithm is competitive in terms of signal to noise ratio and almost in all cases is superior to the state of the art filters in terms of structure similarity.

Research paper thumbnail of Improved HSI Color Space for Color Image Segmentation

Lecture Notes in Computer Science, 2012

We present an interactive, semiautomatic image segmentation method that processes the color infor... more We present an interactive, semiautomatic image segmentation method that processes the color information of each pixel as a unit, thus avoiding color information scattering. The color information of every pixel is integrated in the segmented image by an adaptive color similarity function designed for direct color comparisons. The border between the achromatic and chromatic zones in the HSI color model has been transformed in order to improve the quality of the pixels segmentation when their colors are very obscure and very clear. The color integrating technique is direct, simple and computationally inexpensive, and it has also good performance in low chromaticity and low contrast images. It is shown that segmentation accuracy is above 95% as average and that the method is fast. These results are significant when compared to other solutions found in the current literature.

Research paper thumbnail of The design of color, raster-scan graphical displays for process control applications

MTA Számítástechnikai és Automatizálási Kutató Intézet eBooks, 1976

Additionally, many other subjects not intimately related with process control display systems hav... more Additionally, many other subjects not intimately related with process control display systems have not been discussed in this study. They are adequately analyzed and discussed in many other articles in the literature ell,

Research paper thumbnail of A Novel Approach to Automatic Color Matching

Springer eBooks, 2006

In this paper the design and operation of an Automatic Color Matching system is presented. This n... more In this paper the design and operation of an Automatic Color Matching system is presented. This novel system takes advantage of the improvements introduced by Alpha-Beta associative memories, an efficient, unconventional model of associative memory of recent creation. The results are demonstrated through experiments on a relatively small database with 1001 samples prepared by the authors. However, the approach is considered valid according to the tendency of the results obtained, in part, thanks to the performance exhibited by Alpha-Beta associative memories.

Research paper thumbnail of Specification problems of a process control display

MTA Számítástechnikai és Automatizálási Kutató Intézet eBooks, 1975

Research paper thumbnail of Images retrieval using wavelets, histograms and sub images

Research on computing science, 2004

Research paper thumbnail of Detection of Human Retina Images Suspect of Glaucoma through the Vascular Bundle Displacement in the Optic Disc

Lecture Notes in Computer Science, 2013

ABSTRACT This work presents a methodology for detecting human retina images suspect of glaucoma b... more ABSTRACT This work presents a methodology for detecting human retina images suspect of glaucoma based on the measurement of displacement of the vascular bundle caused by the growth of the excavation or cup. The results achieved are due to the relative increase in size of the cup or excavation that causes a displacement of the blood vessel bundle to the superior, inferior and nasal optic disc areas. The method consists of the segmentation of the optic disc contour and the vascular bundle located within it, and calculation of its displacement from its normal position using the chessboard metric. The method was successful in 62 images of a total of 67, achieving an accuracy of 93.02% of sensitivity and 91.66% of specificity in the pre-diagnosis.

Research paper thumbnail of Improving Depth Estimation by Embedding Semantic Segmentation: A Hybrid CNN Model

Sensors, Feb 21, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of Color Image Segmentation by Means of a Similarity Function

Lecture Notes in Computer Science, 2010

An interactive, semiautomatic image segmentation method is presented which, unlike most of the ex... more An interactive, semiautomatic image segmentation method is presented which, unlike most of the existing methods in the published literature, processes the color information of each pixel as a unit, thus avoiding color information scattering. The process has two steps: 1) The manual selection of few sample pixels of the color to be segmented, 2) The automatic generation of the so called Color Similarity Image (CSI), which is a gray level image with all the tonalities of the selected color. The color information of every pixel is integrated by a similarity function for direct color comparisons. The color integrating technique is direct, simple, and computationally inexpensive. It is shown that the improvement in quality of our proposed segmentation technique and its quick result is significant with respect to other solutions found in the literature.

Research paper thumbnail of Extraction of Blood Vessels in Ophthalmic Color Images of Human Retinas

Lecture Notes in Computer Science, 2006

This paper presents a strategy for the extraction of blood vessels from ophthalmoscopic color ima... more This paper presents a strategy for the extraction of blood vessels from ophthalmoscopic color images of the fundus of human retinas. To extract the vascular network, morphology operators were used, primarily maximum of openings and sum of valleys, and secondly a reconstruction by dilation from two images obtained using threshold by hysteresis. To extract the skeleton of the resulting vascular network, morphological thinning and pruning algorithms were used. Results obtained represent a starting point for future work related to the detection of anomalies in the vascular network and techniques for personal authentication.

Research paper thumbnail of Optimal Scheduling for the Performance Optimization of SpMV Computation using Machine Learning Techniques

Research paper thumbnail of Robust image registration for analysis of multisource eye fundus images

Journal of intelligent & fuzzy systems, Mar 23, 2024

Research paper thumbnail of Images retrieval using wavelets, histograms and sub images

Research on Computing Science, 2004

Research paper thumbnail of An adaptive color similarity function suitable for image segmentation and its numerical evaluation

Color Research and Application, May 20, 2016

Research paper thumbnail of Leukocytes Detection, Classification and Counting in Smears of Peripheral Blood

Revista mexicana de ingeniería biomédica, 2014

Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniqu... more Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniques of digital image processing, we developed a computational system platform-independent, which is able to identify, to classify and to count five normal types of leukocytes: neutrophils, eosinophils, basophils, monocytes and lymphocytes. It is important to emphasize that this work does not attempt to differentiate between smears of leukocytes coming from healthy and sick people; this is because most diseases produce a change in the differential count of leukocytes rather than in theirs forms. In the other side, the system could be used in emerging areas such as the topographic hematology and the chronobiology. Automatic classifier of leukocytes, k-NN, Minkowski metric, Pattern recognition, Digital image processing.

Research paper thumbnail of Leukocytes Detection, Classification and Counting in Smears of Peripheral Blood

Revista mexicana de ingeniería biomédica, 2014

Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniqu... more Using the k-NN classifier in combination with the first Minkowski metric, in addition to techniques of digital image processing, we developed a computational system platform-independent, which is able to identify, to classify and to count five normal types of leukocytes: neutrophils, eosinophils, basophils, monocytes and lymphocytes. It is important to emphasize that this work does not attempt to differentiate between smears of leukocytes coming from healthy and sick people; this is because most diseases produce a change in the differential count of leukocytes rather than in theirs forms. In the other side, the system could be used in emerging areas such as the topographic hematology and the chronobiology. Automatic classifier of leukocytes, k-NN, Minkowski metric, Pattern recognition, Digital image processing.

Research paper thumbnail of Image Retrieval Based on Wavelet Transform and Neural Network Classification

Computación Y Sistemas, Dec 31, 2007

The problem of retrieving images from a database is considered. In particular, we retrieve images... more The problem of retrieving images from a database is considered. In particular, we retrieve images belonging to one of the following six categories: 1) commercial planes in land, 2) commercial planes in air, 3) war planes in land, 4) war planes in air, 5) small aircraft in land, and 6) small aircraft in the air. During training, a wavelet-based description of each image is first calculated using Daubechies 4-wavelet transformation. The resulting coefficients are used to train a neural network (NN). During classification, test images are treated by the already trained NN. Three different ways to obtain the coefficients of the Daubechies transform were proposed and tested: from the entire image color channels, from the histogram of the biggest circular window inside the image color channels, and from the histograms of the square sub-images in the image color channels of the original image. 120 images were used for training and 240 for testing. The best efficiency of 88% was obtained with the third method.

Research paper thumbnail of Reconocimiento de rostros mediante estructuras faciales antropométricas

Research in Computing Science, Dec 31, 2018

Resumen. Las estructuras faciales antropométricas son estructuras que se obtienen mediante puntos... more Resumen. Las estructuras faciales antropométricas son estructuras que se obtienen mediante puntos somatométricos (los cuales son empleados para la extracción de características craneofaciales). En este trabajo se propone una estructura facial antropométrica que contribuya al desarrollo de un método que realice reconocimiento de rostros de manera automática. Este método está basado principalmente en cinco etapas: extracción de coordenadas de los puntos somatométricos, creación de la estructura antropométrica, cálculo de distancias entre puntos, detección deángulos de los puntos y cálculo de proporciones respecto a las distancias. Las distancias y losángulos se obtienen con base en la relación de los puntos, relación que es establecida con la estructura antropométrica propuesta. A diferencia de otros trabajos relacionados con el reconocimiento de rostros, el método propuesto utiliza solamente nueve puntos, lo que es, hasta ahora, uno de los menores números de puntos utilizados.

Research paper thumbnail of Influence of Luminance L* in the L*a*b* Color Space during Color Segmentation in Highly Saturated Color Images

Research in Computing Science, Dec 31, 2015

In this paper a study of the influence of luminance L* at the CIE L* a* b* color space during col... more In this paper a study of the influence of luminance L* at the CIE L* a* b* color space during color segmentation in highly saturated color images is presented. A comparative study is made between the behavior of segmentation in color images using (1) the Euclidean metric of the RGB channels (2) the Euclidean metric of a* and b* in CIE L*a*b* color space and (3) an adaptive color similarity function defined as a product of Gaussian functions in a modified HSI color space. For the evaluation, synthetic images were particularly designed to accurately assess the performance of the color segmentation. The testing system can be used either to explore the behavior of a similarity function (or metric) in different color spaces or to explore different metrics (or similarity functions) in the same color space. From the results it was obtained that the color parameters a* and b* are not independent of the luminance parameter L* as one might initially assume. In the majority of cases the CIE L*a*b color space was more influenced by the faded shadow than the RGB color space. The segmentation using the Euclidean metric in L*a*b* color space suffered errors in all cases. It manifested in different degrees and at different levels of faded shadow (less than 10% to 80%).

Research paper thumbnail of An Adaptive Color Similarity Function for Color Image Segmentation

Lecture Notes in Computer Science, 2011

In this paper an interactive, semiautomatic image segmentation method is presented which, process... more In this paper an interactive, semiautomatic image segmentation method is presented which, processes the color information of each pixel as a unit, thus avoiding color information scattering. The process has only two steps: 1) The manual selection of few sample pixels of the color to be segmented in the image; and 2) The automatic generation of the so called Color Similarity Image (CSI), which is just a gray level image with all the tonalities of the selected colors. The color information of every pixel is integrated in the segmented image by an adaptive color similarity function designed for direct color comparisons. The color integrating technique is direct, simple, and computationally inexpensive and it has also good performance in gray level and low contrast images.

Research paper thumbnail of Image Filter Based on Block Matching, Discrete Cosine Transform and Principal Component Analysis

Lecture Notes in Computer Science, 2017

An algorithm for filtering the images contaminated by additive white Gaussian noise is proposed. ... more An algorithm for filtering the images contaminated by additive white Gaussian noise is proposed. The algorithm uses the groups of Hadamard transformed patches of discrete cosine coefficients to reject noisy components according to Wiener filtering approach. The groups of patches are found by the proposed block similarity search algorithm of reduced complexity performed on block patches in transform domain. When the noise variance is small, the proposed filter uses an additional stage based on principal component analysis; otherwise the experimental Wiener filtering is performed. The obtained filtering results are compared to the state of the art filters in terms of peak signal-to-noise ratio and structure similarity index. It is shown that the proposed algorithm is competitive in terms of signal to noise ratio and almost in all cases is superior to the state of the art filters in terms of structure similarity.

Research paper thumbnail of Improved HSI Color Space for Color Image Segmentation

Lecture Notes in Computer Science, 2012

We present an interactive, semiautomatic image segmentation method that processes the color infor... more We present an interactive, semiautomatic image segmentation method that processes the color information of each pixel as a unit, thus avoiding color information scattering. The color information of every pixel is integrated in the segmented image by an adaptive color similarity function designed for direct color comparisons. The border between the achromatic and chromatic zones in the HSI color model has been transformed in order to improve the quality of the pixels segmentation when their colors are very obscure and very clear. The color integrating technique is direct, simple and computationally inexpensive, and it has also good performance in low chromaticity and low contrast images. It is shown that segmentation accuracy is above 95% as average and that the method is fast. These results are significant when compared to other solutions found in the current literature.

Research paper thumbnail of The design of color, raster-scan graphical displays for process control applications

MTA Számítástechnikai és Automatizálási Kutató Intézet eBooks, 1976

Additionally, many other subjects not intimately related with process control display systems hav... more Additionally, many other subjects not intimately related with process control display systems have not been discussed in this study. They are adequately analyzed and discussed in many other articles in the literature ell,

Research paper thumbnail of A Novel Approach to Automatic Color Matching

Springer eBooks, 2006

In this paper the design and operation of an Automatic Color Matching system is presented. This n... more In this paper the design and operation of an Automatic Color Matching system is presented. This novel system takes advantage of the improvements introduced by Alpha-Beta associative memories, an efficient, unconventional model of associative memory of recent creation. The results are demonstrated through experiments on a relatively small database with 1001 samples prepared by the authors. However, the approach is considered valid according to the tendency of the results obtained, in part, thanks to the performance exhibited by Alpha-Beta associative memories.

Research paper thumbnail of Specification problems of a process control display

MTA Számítástechnikai és Automatizálási Kutató Intézet eBooks, 1975

Research paper thumbnail of Images retrieval using wavelets, histograms and sub images

Research on computing science, 2004

Research paper thumbnail of Detection of Human Retina Images Suspect of Glaucoma through the Vascular Bundle Displacement in the Optic Disc

Lecture Notes in Computer Science, 2013

ABSTRACT This work presents a methodology for detecting human retina images suspect of glaucoma b... more ABSTRACT This work presents a methodology for detecting human retina images suspect of glaucoma based on the measurement of displacement of the vascular bundle caused by the growth of the excavation or cup. The results achieved are due to the relative increase in size of the cup or excavation that causes a displacement of the blood vessel bundle to the superior, inferior and nasal optic disc areas. The method consists of the segmentation of the optic disc contour and the vascular bundle located within it, and calculation of its displacement from its normal position using the chessboard metric. The method was successful in 62 images of a total of 67, achieving an accuracy of 93.02% of sensitivity and 91.66% of specificity in the pre-diagnosis.

Research paper thumbnail of Improving Depth Estimation by Embedding Semantic Segmentation: A Hybrid CNN Model

Sensors, Feb 21, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Research paper thumbnail of Color Image Segmentation by Means of a Similarity Function

Lecture Notes in Computer Science, 2010

An interactive, semiautomatic image segmentation method is presented which, unlike most of the ex... more An interactive, semiautomatic image segmentation method is presented which, unlike most of the existing methods in the published literature, processes the color information of each pixel as a unit, thus avoiding color information scattering. The process has two steps: 1) The manual selection of few sample pixels of the color to be segmented, 2) The automatic generation of the so called Color Similarity Image (CSI), which is a gray level image with all the tonalities of the selected color. The color information of every pixel is integrated by a similarity function for direct color comparisons. The color integrating technique is direct, simple, and computationally inexpensive. It is shown that the improvement in quality of our proposed segmentation technique and its quick result is significant with respect to other solutions found in the literature.

Research paper thumbnail of Extraction of Blood Vessels in Ophthalmic Color Images of Human Retinas

Lecture Notes in Computer Science, 2006

This paper presents a strategy for the extraction of blood vessels from ophthalmoscopic color ima... more This paper presents a strategy for the extraction of blood vessels from ophthalmoscopic color images of the fundus of human retinas. To extract the vascular network, morphology operators were used, primarily maximum of openings and sum of valleys, and secondly a reconstruction by dilation from two images obtained using threshold by hysteresis. To extract the skeleton of the resulting vascular network, morphological thinning and pruning algorithms were used. Results obtained represent a starting point for future work related to the detection of anomalies in the vascular network and techniques for personal authentication.