Proceedings of the Institute for System Programming of the RAS, 2021
Globalization urges the necessity of having world class leaders, and very frequently in its forma... more Globalization urges the necessity of having world class leaders, and very frequently in its formation, is required to teach them computational tools to mainly improve their project management facilities. In order to give project management a greater quality, a very important point is to control and follow up all users’ diverse requirements, from the beginning to the end of each or any type of project: administrative, academic, engineering, software, video games, virtual and mixed reality, etc. This research shows a project requirements manager’s approach which allows knowing the specific requirements in each of its phases and give an advanced description of its various types and their traceability. This prototype promotes project requirement management best practices, and link them to the various areas of engineering, administration, planning and also with society, industry, commerce and academic sectors.
El uso de las imágenes digitales en numerosas esferas de la sociedad es una actividad que ha alca... more El uso de las imágenes digitales en numerosas esferas de la sociedad es una actividad que ha alcanzado un auge notable en los últimos años debido fundamentalmente al gran desarrollo que ha ocurrido en la tecnología a nivel mundial. En la actualidad este tipo de imágenes tienen un gran uso en muchas de las ramas de la medicina pues facilitan el diagnóstico por parte de los especialistas y de esta manera contribuyen a que los pacientes sean diagnosticados mucho antes de que los síntomas de las enfermedades comiencen a manifestarse. En el caso de la Oftalmología una de las imágenes más usadas son las retinografías digitales, las cuales si son utilizadas correctamente le permiten al oftalmólogo detectar la aparición de enfermedades como la glaucoma y la retinopatía diabética. Uno de los elementos que se puede apreciar en estas es el disco óptico o papila óptica, cuya localización y detección tiene vital importancia para trabajar con diferentes partes de la estructura del ojo. En este trabajo se proponen dos técnicas para la localización del disco óptico en retinografías digitales que se basan en la combinación de varios filtros y la aplicación de operaciones lógicas. Para realizar la prueba de los algoritmos se utilizaron las bases de datos DRIVE
Depth reconstruction from single images has been a challenging task due to the complexity and the... more Depth reconstruction from single images has been a challenging task due to the complexity and the quantity of depth cues that images have. Convolutional Neural Networks (CNN) have been successfully used to reconstruct depth of general object scenes; however, these works have not been tailored for the particular problem of road perspective depth reconstruction. As we aim to build a computational efficient model, we focus on single-stage CNNs. In this paper we propose two different models for solving this task. A particularity is that our models perform refinement in the same single-stage training; thus, we call them Reduce-Refine-Upsample (RRU) models because of the order of the CNN operations. We compare our models with the current state of the art in depth reconstruction, obtaining improvements in both global and local views for images of road perspectives.
The task consists in estimating the personality traits of users from their handwritten texts. To ... more The task consists in estimating the personality traits of users from their handwritten texts. To classify them, we use the scanned image of the subject hand-written essay divided in patches and we propose in this work an architecture based on a Convolutional Neural Network (CNN) as classifier. The original dataset consists of 418 images in color, from which we obtained 216 patches of each image in grayscale and then we binarized them resulting in approximately 90,000 images. The CNN consists of five convolutional layers to extract features of the patches and three fully connected layers to perform the classification.
Computación y Sistemas (México) Num.3 Vol.11, Dec 31, 2008
The goal of this paper is to document the use of time series in color matching. Although time ser... more The goal of this paper is to document the use of time series in color matching. Although time series are not commonly used for this purpose, the results obtained, based on the principle of similarity in time series using the Euclidean distance, establish the validity of its use for color matching applications. The accuracy of color matching was based on the measures of reflectivity versus wavelength of samples given by a spectrophotometer. The error estimation was calculated using a database of 1001 elements. The matching module has been tested with six samples included and not included in the database. All of them gave an error lower than the estimated absolute error of 11.36.
This paper presents an approach for enhancing digital color images printed in halftoning. The met... more This paper presents an approach for enhancing digital color images printed in halftoning. The method, which we call Selective Conditional Enhancement, has been applied with good results to enhance digital color images printed in halftone. Due to the repetitive nature of the process for image digitizing and the common structure of patterns used to create halftone in color images, it has been observed that the alterations of pixel colors, in general, are also repetitive. Based on the frequency of occurrence of pixels of a given color, and on the values of their Red-Green-Blue (RGB) components, we have defined eight heuristic rules. In principle, these rules define as valid those pixels having a high frequency of occurrence and as artifacts those with low frequency of occurrence. The color of less frequent artifacts is then changed to some color of any more frequent valid pixel. This approach, based also on user-defined essential colors, generates images that are notably enhanced.
We present a fast, efficient, and automatic method for extracting vessels from retinal images. Th... more We present a fast, efficient, and automatic method for extracting vessels from retinal images. The proposed method is based on the second local entropy and on the gray-level co-occurrence matrix (GLCM). The algorithm is designed to have flexibility in the definition of the blood vessel contours. Using information from the GLCM, a statistic feature is calculated to act as a threshold value. The performance of the proposed approach was evaluated in terms of its sensitivity, specificity, and accuracy. The results obtained for these metrics were 0.9648, 0.9480, and 0.9759, respectively. These results show the high performance and accuracy that the proposed method offers. Another aspect evaluated in this method is the elapsed time to carry out the segmentation. The average time required by the proposed method is 3 s for images of size 565 9 584 pixels. To assess the ability and speed of the proposed method, the experimental results are compared with those obtained using other existing methods. Keywords Retinal image analysis Á Blood vessel network Á Image segmentation Á Fast automated analysis Á Co-occurrence matrix Á Entropy thresholding 1 Introduction Retinal or fundus images provide information about the blood supply system to the retina. Accurate blood vessel segmentation is fundamental in the analysis of fundus images since further analysis usually depends on the accuracy of this segmentation (Chaudhuri et al. 1989). It is therefore desirable to provide ways of automating the process of the analysis of fundus images, using computerized image analysis, so as to provide at least preliminary screening information and also as an aid to diagnosis to assist the clinician in the analysis of difficult cases.
This paper presents an approach for enhancing digital color images printed in halftoning. The met... more This paper presents an approach for enhancing digital color images printed in halftoning. The method, which we call Selective Conditional Enhancement, has been applied with good results to enhance digital color images printed in halftone. Due to the repetitive nature of the process for image digitizing and the common structure of patterns used to create halftone in color images, it has been observed that the alterations of pixel colors, in general, are also repetitive. Based on the frequency of occurrence of pixels of a given color, and on the values of their Red-Green-Blue (RGB) components, we have defined eight heuristic rules. In principle, these rules define as valid those pixels having a high frequency of occurrence and as artifacts those with low frequency of occurrence. The color of less frequent artifacts is then changed to some color of any more frequent valid pixel. This approach, based also on user-defined essential colors, generates images that are notably enhanced.
Glaucoma detection is an important task, as this disease can affect the optic nerve, and this cou... more Glaucoma detection is an important task, as this disease can affect the optic nerve, and this could lead to blindness. This can be prevented with early diagnosis, periodic controls, and treatment so that it can be stopped and prevent visual loss. Usually, the detection of glaucoma is carried out through various examinations such as tonometry, gonioscopy, pachymetry, etc. In this work, we carry out this detection by using images obtained through retinal cameras, in which we can observe the state of the optic nerve. This work addresses an accurate diagnostic methodology based on Convolutional Neural Networks (CNNs) to classify these optical images. Most works require a large number of images to train their CNN architectures, and most of them use the whole image to perform the classification. We will use a small dataset containing 366 examples to train the proposed CNN architecture and we will only focus on the analysis of the optic disc by extracting it from the full image, as this is...
En el mundo globalizado se requiere contar con ingenieros líderes de proyectos, que puedan realiz... more En el mundo globalizado se requiere contar con ingenieros líderes de proyectos, que puedan realizar labores de evaluadores de proyectos con éxito. El sistema propuesto permite hacer un análisis comparativo de los diferentes proyectos participantes en eventos de invención, innovación y creatividad, basados en sus características de calidad en uso, funcionalidad y usabilidad, mediante un plan de métricas externas y de calidad en uso. El modelo está basado en normas internacionales (ISO/IEC 9126, 14598, IEEE 1061) y modelos mexicanos (MECHDAV), y software propuesto, es desarrollado en un ambiente visual WEB, para dispositivos móviles (tabletas), permiten evaluar genéricamente la calidad de los proyectos-productos-servicios que participan en los concursos mencionados; este sistema proporciona un soporte a las personas evaluadoras (jurados) para emitir dictámenes imparciales con mayor precisión cuantitativa. Este sistema está dirigido a organizaciones, empresas y usuarios finales que n...
Depth reconstruction from single monocular images has been a challenging task due to the complexi... more Depth reconstruction from single monocular images has been a challenging task due to the complexity and the quantity of depth cues that images have. Convolutional Neural Networks (CNN) have been successfully used to reconstruct depth of general object scenes; however, proposed works use several stages of training which make this process more complex and time consuming. As we aim to build a computational efficient model, we focus on single-stage training CNN. In this paper, we propose five different models for solving this task, ranging from a simple convolutional network, to one with residual, convolutional, refinement and upsampling layers. We compare our models with the current state of the art in depth reconstruction and measure depth reconstruction error for different datasets (KITTI, NYU), obtaining improvements in both global and local error measures.
A CAPTCHA is a program that allows or denies access to services by generating and grading test th... more A CAPTCHA is a program that allows or denies access to services by generating and grading test that humans can pass but current computer programs cannot. Captchas are generally used to protect free web services from automated programs. Also, they can provide an idea of which fields in artificial intelligence are the most explored and which could be researched in the near future. Most of the tests that are based on text recognition have been broken by optical character recognition (OCR) techniques while those based on images are vulnerable to machine learning attacks. Humans make use of cognitive abilities to carry out tasks in daily life, even if they are not conscious which ones or how they use them. The current state of technology is still not enough to reproduce some human cognitive abilities, and the identification of those abilities is the basis for the design of new CAPTCHA models. In this paper we introduce seven new models of CAPTCHA to test some cognitive abilities that are supposed to be beyond the capabilities of artificial agents. We use some APIs to proof that images used in the proposals are extremely difficult to be recognized by artificial agents.
Resumen. La reconstrucción de la profundidad a partir de una sola imagen ha sido una tarea difíci... more Resumen. La reconstrucción de la profundidad a partir de una sola imagen ha sido una tarea difícil debido a la complejidad y la cantidad de indicios de profundidad que puede contener una sola imagen. Las Redes Neuronales Convolucionales (RNC) se han utilizado conéxito para reconstruir la profundidad de objetos en escenas generales; sin embargo, estos trabajos no se han adaptado para el problema particular de la reconstrucción de la profundidad a partir de la perspectiva. Nuestra propuesta se basa en construir una RNC computacional eficiente; nos centramos en Redes Neuronales Completamente Convolucionales (RNCC), cuyo entrenamiento requiere de una sola etapa. Comparamos nuestra RNC con el estado del arte actual en reconstrucción de profundidad, obteniendo mejoras en niveles globales para imágenes viales con perspectiva presente.
La detección e identificación de peatones, así como su rastreo, es un problema abierto en el área... more La detección e identificación de peatones, así como su rastreo, es un problema abierto en el área de la visión artificial que se ha atacado de formas muy diversas. Este trabajo presenta una propuesta para la detección de peatones utilizando técnicas de análisis de imágenes para la extracción de características de un peatón basadas en histograma de gradientes orientados y patrones binarios locales los cuales, son extraídos de una región de interés previamente detectada, combinados e ingresados a una máquina de soporte vectorial que funge como clasificador entre muestras de peatones y no peatones. Un rastreador basado en el algoritmo MeanShift es implementado por su eficiencia en el procesamiento del rastreo y la identificación de las nuevas ubicaciones de cada uno de los objetivos detectados.
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.
Proceedings of the Institute for System Programming of the RAS, 2021
Globalization urges the necessity of having world class leaders, and very frequently in its forma... more Globalization urges the necessity of having world class leaders, and very frequently in its formation, is required to teach them computational tools to mainly improve their project management facilities. In order to give project management a greater quality, a very important point is to control and follow up all users’ diverse requirements, from the beginning to the end of each or any type of project: administrative, academic, engineering, software, video games, virtual and mixed reality, etc. This research shows a project requirements manager’s approach which allows knowing the specific requirements in each of its phases and give an advanced description of its various types and their traceability. This prototype promotes project requirement management best practices, and link them to the various areas of engineering, administration, planning and also with society, industry, commerce and academic sectors.
El uso de las imágenes digitales en numerosas esferas de la sociedad es una actividad que ha alca... more El uso de las imágenes digitales en numerosas esferas de la sociedad es una actividad que ha alcanzado un auge notable en los últimos años debido fundamentalmente al gran desarrollo que ha ocurrido en la tecnología a nivel mundial. En la actualidad este tipo de imágenes tienen un gran uso en muchas de las ramas de la medicina pues facilitan el diagnóstico por parte de los especialistas y de esta manera contribuyen a que los pacientes sean diagnosticados mucho antes de que los síntomas de las enfermedades comiencen a manifestarse. En el caso de la Oftalmología una de las imágenes más usadas son las retinografías digitales, las cuales si son utilizadas correctamente le permiten al oftalmólogo detectar la aparición de enfermedades como la glaucoma y la retinopatía diabética. Uno de los elementos que se puede apreciar en estas es el disco óptico o papila óptica, cuya localización y detección tiene vital importancia para trabajar con diferentes partes de la estructura del ojo. En este trabajo se proponen dos técnicas para la localización del disco óptico en retinografías digitales que se basan en la combinación de varios filtros y la aplicación de operaciones lógicas. Para realizar la prueba de los algoritmos se utilizaron las bases de datos DRIVE
Depth reconstruction from single images has been a challenging task due to the complexity and the... more Depth reconstruction from single images has been a challenging task due to the complexity and the quantity of depth cues that images have. Convolutional Neural Networks (CNN) have been successfully used to reconstruct depth of general object scenes; however, these works have not been tailored for the particular problem of road perspective depth reconstruction. As we aim to build a computational efficient model, we focus on single-stage CNNs. In this paper we propose two different models for solving this task. A particularity is that our models perform refinement in the same single-stage training; thus, we call them Reduce-Refine-Upsample (RRU) models because of the order of the CNN operations. We compare our models with the current state of the art in depth reconstruction, obtaining improvements in both global and local views for images of road perspectives.
The task consists in estimating the personality traits of users from their handwritten texts. To ... more The task consists in estimating the personality traits of users from their handwritten texts. To classify them, we use the scanned image of the subject hand-written essay divided in patches and we propose in this work an architecture based on a Convolutional Neural Network (CNN) as classifier. The original dataset consists of 418 images in color, from which we obtained 216 patches of each image in grayscale and then we binarized them resulting in approximately 90,000 images. The CNN consists of five convolutional layers to extract features of the patches and three fully connected layers to perform the classification.
Computación y Sistemas (México) Num.3 Vol.11, Dec 31, 2008
The goal of this paper is to document the use of time series in color matching. Although time ser... more The goal of this paper is to document the use of time series in color matching. Although time series are not commonly used for this purpose, the results obtained, based on the principle of similarity in time series using the Euclidean distance, establish the validity of its use for color matching applications. The accuracy of color matching was based on the measures of reflectivity versus wavelength of samples given by a spectrophotometer. The error estimation was calculated using a database of 1001 elements. The matching module has been tested with six samples included and not included in the database. All of them gave an error lower than the estimated absolute error of 11.36.
This paper presents an approach for enhancing digital color images printed in halftoning. The met... more This paper presents an approach for enhancing digital color images printed in halftoning. The method, which we call Selective Conditional Enhancement, has been applied with good results to enhance digital color images printed in halftone. Due to the repetitive nature of the process for image digitizing and the common structure of patterns used to create halftone in color images, it has been observed that the alterations of pixel colors, in general, are also repetitive. Based on the frequency of occurrence of pixels of a given color, and on the values of their Red-Green-Blue (RGB) components, we have defined eight heuristic rules. In principle, these rules define as valid those pixels having a high frequency of occurrence and as artifacts those with low frequency of occurrence. The color of less frequent artifacts is then changed to some color of any more frequent valid pixel. This approach, based also on user-defined essential colors, generates images that are notably enhanced.
We present a fast, efficient, and automatic method for extracting vessels from retinal images. Th... more We present a fast, efficient, and automatic method for extracting vessels from retinal images. The proposed method is based on the second local entropy and on the gray-level co-occurrence matrix (GLCM). The algorithm is designed to have flexibility in the definition of the blood vessel contours. Using information from the GLCM, a statistic feature is calculated to act as a threshold value. The performance of the proposed approach was evaluated in terms of its sensitivity, specificity, and accuracy. The results obtained for these metrics were 0.9648, 0.9480, and 0.9759, respectively. These results show the high performance and accuracy that the proposed method offers. Another aspect evaluated in this method is the elapsed time to carry out the segmentation. The average time required by the proposed method is 3 s for images of size 565 9 584 pixels. To assess the ability and speed of the proposed method, the experimental results are compared with those obtained using other existing methods. Keywords Retinal image analysis Á Blood vessel network Á Image segmentation Á Fast automated analysis Á Co-occurrence matrix Á Entropy thresholding 1 Introduction Retinal or fundus images provide information about the blood supply system to the retina. Accurate blood vessel segmentation is fundamental in the analysis of fundus images since further analysis usually depends on the accuracy of this segmentation (Chaudhuri et al. 1989). It is therefore desirable to provide ways of automating the process of the analysis of fundus images, using computerized image analysis, so as to provide at least preliminary screening information and also as an aid to diagnosis to assist the clinician in the analysis of difficult cases.
This paper presents an approach for enhancing digital color images printed in halftoning. The met... more This paper presents an approach for enhancing digital color images printed in halftoning. The method, which we call Selective Conditional Enhancement, has been applied with good results to enhance digital color images printed in halftone. Due to the repetitive nature of the process for image digitizing and the common structure of patterns used to create halftone in color images, it has been observed that the alterations of pixel colors, in general, are also repetitive. Based on the frequency of occurrence of pixels of a given color, and on the values of their Red-Green-Blue (RGB) components, we have defined eight heuristic rules. In principle, these rules define as valid those pixels having a high frequency of occurrence and as artifacts those with low frequency of occurrence. The color of less frequent artifacts is then changed to some color of any more frequent valid pixel. This approach, based also on user-defined essential colors, generates images that are notably enhanced.
Glaucoma detection is an important task, as this disease can affect the optic nerve, and this cou... more Glaucoma detection is an important task, as this disease can affect the optic nerve, and this could lead to blindness. This can be prevented with early diagnosis, periodic controls, and treatment so that it can be stopped and prevent visual loss. Usually, the detection of glaucoma is carried out through various examinations such as tonometry, gonioscopy, pachymetry, etc. In this work, we carry out this detection by using images obtained through retinal cameras, in which we can observe the state of the optic nerve. This work addresses an accurate diagnostic methodology based on Convolutional Neural Networks (CNNs) to classify these optical images. Most works require a large number of images to train their CNN architectures, and most of them use the whole image to perform the classification. We will use a small dataset containing 366 examples to train the proposed CNN architecture and we will only focus on the analysis of the optic disc by extracting it from the full image, as this is...
En el mundo globalizado se requiere contar con ingenieros líderes de proyectos, que puedan realiz... more En el mundo globalizado se requiere contar con ingenieros líderes de proyectos, que puedan realizar labores de evaluadores de proyectos con éxito. El sistema propuesto permite hacer un análisis comparativo de los diferentes proyectos participantes en eventos de invención, innovación y creatividad, basados en sus características de calidad en uso, funcionalidad y usabilidad, mediante un plan de métricas externas y de calidad en uso. El modelo está basado en normas internacionales (ISO/IEC 9126, 14598, IEEE 1061) y modelos mexicanos (MECHDAV), y software propuesto, es desarrollado en un ambiente visual WEB, para dispositivos móviles (tabletas), permiten evaluar genéricamente la calidad de los proyectos-productos-servicios que participan en los concursos mencionados; este sistema proporciona un soporte a las personas evaluadoras (jurados) para emitir dictámenes imparciales con mayor precisión cuantitativa. Este sistema está dirigido a organizaciones, empresas y usuarios finales que n...
Depth reconstruction from single monocular images has been a challenging task due to the complexi... more Depth reconstruction from single monocular images has been a challenging task due to the complexity and the quantity of depth cues that images have. Convolutional Neural Networks (CNN) have been successfully used to reconstruct depth of general object scenes; however, proposed works use several stages of training which make this process more complex and time consuming. As we aim to build a computational efficient model, we focus on single-stage training CNN. In this paper, we propose five different models for solving this task, ranging from a simple convolutional network, to one with residual, convolutional, refinement and upsampling layers. We compare our models with the current state of the art in depth reconstruction and measure depth reconstruction error for different datasets (KITTI, NYU), obtaining improvements in both global and local error measures.
A CAPTCHA is a program that allows or denies access to services by generating and grading test th... more A CAPTCHA is a program that allows or denies access to services by generating and grading test that humans can pass but current computer programs cannot. Captchas are generally used to protect free web services from automated programs. Also, they can provide an idea of which fields in artificial intelligence are the most explored and which could be researched in the near future. Most of the tests that are based on text recognition have been broken by optical character recognition (OCR) techniques while those based on images are vulnerable to machine learning attacks. Humans make use of cognitive abilities to carry out tasks in daily life, even if they are not conscious which ones or how they use them. The current state of technology is still not enough to reproduce some human cognitive abilities, and the identification of those abilities is the basis for the design of new CAPTCHA models. In this paper we introduce seven new models of CAPTCHA to test some cognitive abilities that are supposed to be beyond the capabilities of artificial agents. We use some APIs to proof that images used in the proposals are extremely difficult to be recognized by artificial agents.
Resumen. La reconstrucción de la profundidad a partir de una sola imagen ha sido una tarea difíci... more Resumen. La reconstrucción de la profundidad a partir de una sola imagen ha sido una tarea difícil debido a la complejidad y la cantidad de indicios de profundidad que puede contener una sola imagen. Las Redes Neuronales Convolucionales (RNC) se han utilizado conéxito para reconstruir la profundidad de objetos en escenas generales; sin embargo, estos trabajos no se han adaptado para el problema particular de la reconstrucción de la profundidad a partir de la perspectiva. Nuestra propuesta se basa en construir una RNC computacional eficiente; nos centramos en Redes Neuronales Completamente Convolucionales (RNCC), cuyo entrenamiento requiere de una sola etapa. Comparamos nuestra RNC con el estado del arte actual en reconstrucción de profundidad, obteniendo mejoras en niveles globales para imágenes viales con perspectiva presente.
La detección e identificación de peatones, así como su rastreo, es un problema abierto en el área... more La detección e identificación de peatones, así como su rastreo, es un problema abierto en el área de la visión artificial que se ha atacado de formas muy diversas. Este trabajo presenta una propuesta para la detección de peatones utilizando técnicas de análisis de imágenes para la extracción de características de un peatón basadas en histograma de gradientes orientados y patrones binarios locales los cuales, son extraídos de una región de interés previamente detectada, combinados e ingresados a una máquina de soporte vectorial que funge como clasificador entre muestras de peatones y no peatones. Un rastreador basado en el algoritmo MeanShift es implementado por su eficiencia en el procesamiento del rastreo y la identificación de las nuevas ubicaciones de cada uno de los objetivos detectados.
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.
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