Author: VICENTE ALARCON AQUINO

Algorithmic Error Correction of Impedance Measuring Sensors

VICENTE ALARCON AQUINO (2009)

Chemistry, Analytical; Electrochemistry; Instruments & Instrumentation

Article

CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA

DWT foveation-based multiresolution compression algorithm

JUAN CARLOS GALAN HERNANDEZ VICENTE ALARCON AQUINO OLEG STAROSTENKO BASARAB JUAN MANUEL RAMIREZ CORTES (2010)

Discrete Wavelet Transform (DWT) foveated compression can be used in real-time video processing frameworks for reducing the communication overhead. Such algorithms lead into high rate compression results due to the fact that the information loss is isolated outside a region of interest (ROI). The fovea compression can also be applied to other classic transforms such as the commonly used discrete cosine transform (DCT). An analysis has then been performed showing different error and compression rates for the DWT-based and the DCT-based foveated compression algorithms. Simulation results show that with foveated compression high ratio of compression can be achieved while keeping high quality over the designed ROI.

Article

Foveation Wavelets Wavelet transforms Discrete cosine transform Compression CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

FPGA-based educational platform for real-time image processing experiments

JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL VICENTE ALARCON AQUINO Jorge Martinez_Carballido EMMANUEL MORALES FLORES (2010)

In this paper, an implementation of an educational platform for real-time linear and morphological image filtering using a FPGA NexysII, Xilinx®, Spartan 3E, is described. The system is connected to a USB port of a personal computer, which in that way form a powerful and low-cost design station for educational purposes. The FPGA-based system is accessed through a MATLAB graphical user interface, which handles the communication setup and data transfer. The system allows the students to perform comparisons between results obtained from MATLAB simulations and FPGA-based real-time processing. Concluding remarks derived from course evaluations and lab reports are presented.

Article

Image Processing Hardware Education Filtering CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

Neural networks and SVM-based classification of leukocytes using the morphological pattern spectrum

JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL VICENTE ALARCON AQUINO JESUS ANTONIO GONZALEZ BERNAL ANGEL MARIO GARCIA PEDRERO (2010)

In this paper we present the morphological operator pecstrum, or pattern spectrum, as a feature extractor of discriminating characteristics in microscopic leukocytes images for classification purposes. Pecstrum provides an excellent quantitative analysis to model the morphological evolution of nuclei in blood white cells, or leukocytes. According to their maturity stage, leukocytes have been classified by medical experts in six categories, from myeloblast to polymorphonuclear corresponding to the youngest and oldest extremes, respectively. A feature vector based on the pattern spectrum, normalized area, and nucleus - cytoplasm area ratio, was tested using a multilayer perceptron neural network trained by backpropagation, and a Support Vector Machine algorithm. Results from Euclidean distance and k-nearest neighbor classifiers are also reported as reference for comparison purposes. A recognition rate of 87% was obtained in the best case, using 36 patterns for training and 18 for testing, with a three-fold validation scheme. Additional experiments exploring larger databases are currently in progress.

Article

CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

A biometric system based on neural networks and SVM using morphological feature extraction from hand-shape images

JUAN MANUEL RAMIREZ CORTES María del Pilar Gómez Gil VICENTE ALARCON AQUINO JOSE MIGUEL DAVID BAEZ LOPEZ ROGERIO ADRIAN ENRIQUEZ CALDERA (2011)

This paper presents a hand-shape biometric system based on a novel feature extraction methodology using the morphological pattern spectrum or pecstrum. Identification experiments were carried out using the obtained feature vectors as an input to some recognition systems using neural networks and support vector machine (SVM) techniques, obtaining in average an identification of 98.5%. The verification case was analyzed through an Euclidean distance classifier, obtaining the acceptance rate (FAR) and false rejection rate (FRR) of the system for some K-fold cross validation experiments. In average, an Equal Error Rate of 2.85% was obtained. The invariance to rotation and position properties of the pecstrum allow the system to avoid a fixed hand position using pegs, as is the case in other reported systems. The results indicate that the pattern spectrum represents a good alternative of feature extraction for biometric applications.

Article

Biometry Pattern spectrum Hand-shape Verification Identification CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

Initialisation and training procedures for wavelet networks applied to chaotic time series

VICENTE ALARCON AQUINO OLEG STAROSTENKO BASARAB JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL EDGAR SALOMON GARCIA TREVIÑO (2010)

Wavelet networks are a class of neural network that take advantage of good localization properties of multi-resolution analysis and combine them with the approximation abilities of neural networks. This kind of networks uses wavelets as activation functions in the hidden layer and a type of back-propagation algorithm is used for its learning. However, the training procedure used for wavelet networks is based on the idea of continuous differentiable wavelets and some of the most powerful and used wavelets do not satisfy this property. In this paper we report an algorithm for initialising and training wavelet networks applied to the approximation of chaotic time series. The proposed algorithm which has its foundations on correlation analysis of signals allows the use of different types of wavelets, namely, Daubechies, Coiflets, and Symmlets. To show this, comparisons are made for chaotic time series approximation between the proposed approach and the typical wavelet network.

Article

Wavelet networks Wavelets Approximation theory Multi-resolution analysis Chaotic time series CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

Biometric cryptosystem based on keystroke dynamics and k-medoids

VICENTE ALARCON AQUINO HECTOR AUGUSTO GARCIA BALEON JUAN MANUEL RAMIREZ CORTES María del Pilar Gómez Gil OLEG STAROSTENKO BASARAB (2011)

An approach for a biometric cryptosystem based on keystroke dynamics and the k-medoids algorithm is proposed. The stages that comprise the approach are training enrollment and user verification. The proposed approach is able to verify the identity of individuals offline avoiding the use of a centralized database. The approach as reported in this paper may be implemented in stand-alone terminals or embedded in password-based systems to increase the security. The performance of the proposed approach is assessed using 20 samples of keystroke dynamics from 20 different users. Simulation results show a false acceptance rate of 2.89% and a false rejection rate of 3.35%. The cryptographic key released by the proposed architecture may be used in several potential applications such as user login, file encryption or even portable authentication to gain access to virtual private networks.

Article

Biometrics Cryptography Keystroke dynamics K-medoids Minkowski distance CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA