Edgardo Manuel Felipe Riverón

Measurement of Parameters of the Optic Disk in Ophthalmoscopic Color Images of Human Retina

The objective of this paper is to measure some important parameters of the optic disk (or optic papilla) in ophthalmoscopic color images of human retinas. The approach consists of locating the optic disk automatically, segmenting its contour and the contour of the depression-like feature caused by glaucoma, called an excavation or cup. Then the corresponding areas are measured to calculate the ratio Cup/Disc and the relative displacement of the centroids of both regions. To achieve these objectives, noise is filtered, luminance is normalized, and a thresholding technique is used. The results obtained will aid the work of ophthalmologists by increasing the quality of automatic diagnosis of glaucoma, one of the main causes of blindness worldwide.

Histograms, wavelets and neural networks applied to image retrieval

We tackle the problem of retrieving images from a database. In particular we are concerned with the problem of retrieving images of airplanes belonging to one of the following six categories: 1) commercial planes on land, 2) commercial planes in the air, 3) war planes on land, 4) war planes in the air, 5) small aircrafts on land, and 6) small aircrafts in the air. During training, a wavelet-based description of each image is first obtained using Daubechies 4-wavelet transformation. The resulting coefficients are then used to train a neural network. During classification, test images are presented to the trained system. The coefficients are obtained from the Daubechies transform from histograms of a decomposition of the image into square sub-images of each channel of the original image. 120 images were used for training and 240 for independent testing. An 88% correct identification rate was obtained.

MECRAD: Model and Tool for the Technical Quality Evaluation of Software Products in Visual Environment

In this document a model and tool named MECRAD, based among others, upon the following standards: ISO/IEC 9126 and 14598, SQUARE Project, IEEE1061 and SUMI is presented. It is a model for the technical evaluation of Rapid Applications Development (RAD) tools in visual environment. It is directed to organizations, companies and final users that need to select, in an effective and easily way, the most appropriate software to develop their applications. A guideline for the concrete instrumentation of the model, such as ranking, presentation and documentation procedures, is giving.. Cases of study were developed and the results are given (Visual Studio.Net, Net Beans, and Eclipse).

Image Noise Filter Based on DCT and Fast Clustering

An algorithm for filtering images contaminated by additive white Gaussian noise in discrete cosine transform domain is proposed. The algorithm uses a clustering stage to obtain mean power spectrum of each cluster. The groups of clusters are found by the proposed fast algorithm based on 2D histograms and watershed transform. In addition to the mean spectrum of each cluster, the local groups of similar patches are found to obtain the local spectrum, and therefore, derive the local Wiener filter frequency response better and perform the collaborative filtering over the groups of patches. The obtained filtering results are compared to the state-of-the-art filters in terms of peak signal-to-noise ratio and structural similarity index. It is shown that the proposed algorithm is competitive in terms of signal-to-noise ratio and in almost all cases is superior to the state-of-the art filters in terms of structural similarity.

CALIDAD EN USO: FUNDAMENTAL EN LA EVALUACIÓN DE PROYECTOS PARA LA FORMACIÓN INGENIERIL DE LÍDERES DE SU ENTORNO

El sistema propuesto permite hacer un analisis comparativo de los diferentes proyectos participantes en eventos de invencion, innovacion y creatividad, basados en sus caracteristicas de calidad en uso, funcionalidad y usabilidad, mediante un plan de metricas externas y de calidad en uso. El modelo esta 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 moviles (tabletas), permiten evaluar genericamente 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 dictamenes imparciales con mayor precision cuantitativa. Este sistema esta dirigido a organizaciones, empresas y usuarios finales que necesiten seleccionar, facilmente, los proyectos desarrollados con mas calidad, para ser los ganadores en estos concursos. Se proporciona una guia para la instrumentacion concreta de la evaluacion, asi como sus rangos, la presentacion, procedimientos y documentacion. Palabras clave: modelo de calidad, evaluacion tecnica de proyectos-productos; concurso de creatividad, calidad en uso, metricas externas.

Signal Analysis for Assessment and Prediction of the Artificial Habitat in Shrimp Aquaculture

This paper presents a novel work for prediction of artificial habitat in shrimp aquaculture based on environmental signal analysis. The physical-chemical variables that are involved into the system are studied for modeling and predicting environmental patterns.The prediction model is built using AR models that reconstruct a partial section of a particular measured signal. The physical-chemical variables are classified based on the negative ecological impact using a new statistical model that calculates the frequency and the deviation of the measurements. A fuzzy inference system processes the level classifications using aquaculture rules that define all the cases calculating the condition of the shrimp habitat.

Speech recognition using energy, MFCCs and rho parameters to classify syllables in the spanish language

This paper presents an approach for the automatic speech re-cognition using syllabic units. Its segmentation is based on using the Short-Term Total Energy Function (STTEF) and the Energy Function of the High Frequency (ERO parameter) higher than 3,5 KHz of the speech signal. Training for the classification of the syllables is based on ten related Spanish language rules for syllable splitting. Recognition is based on a Continuous Density Hidden Markov Models and the bigram model language. The approach was tested using two voice corpus of natural speech, one constructed for researching in our laboratory (experimental) and the other one, the corpus Latino40 commonly used in speech researches. The use of ERO and MFCCs parameter increases speech recognition by 5.5% when compared with recognition using STTEF in discontinuous speech and improved more than 2% in continuous speech with three states. When the number of states is incremented to five, the recognition rate is improved proportionally to 98% for the discontinuous speech and to 81% for the continuous one.

Speech recognition using energy parameters to classify syllables in the spanish language

This paper presents an approach for the automatic speech re-cognition using syllabic units. Its segmentation is based on using the Short-Term Total Energy Function (STTEF) and the Energy Function of the High Frequency (ERO parameter) higher than 3,5 KHz of the speech signal. Training for the classification of the syllables is based on ten related Spanish language rules for syllable splitting. Recognition is based on a Continuous Density Hidden Markov Models and the bigram model language. The approach was tested using two voice corpus of natural speech, one constructed for researching in our laboratory (experimental) and the other one, the corpus Latino40 commonly used in speech researches. The use of ERO parameter increases speech recognition by 5% when compared with recognition using STTEF in discontinuous speech and improved more than 1.5% in continuous speech with three states. When the number of states is incremented to five, the recognition rate is improved proportionally to 97.5% for the discontinuous speech and to 80.5% for the continuous one.