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Author: JUAN MANUEL RAMIREZ CORTES

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

On digital signal processing understanding through simulation and animation tools

JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL ROGERIO ADRIAN ENRIQUEZ CALDERA (2008)

This paper describes the use of simulation and animation tools based on MathCAD, aimed to support the understanding of basic principles of digital filters. An important feature is the interaction student-computer to simulate different problems with parameter changes and its instantaneous evaluation by the software, which motivates the reasoning and understanding of the mathematical concepts by the student. In addition, the animation options in MathCAD allow the students to create virtual environments which resemble the real instrumentation procedures in the laboratory, such as the typical frequency sweep based on a signal generator and the oscilloscope. A collection of different study cases in the area of digital signal processing such as filter design, Nyquist criterium, digital filtering in the time domain by difference equations, relation to frequency response in both, continuous and discrete domains, and modulation, is described.

Article

Digital signal processing Digital filters Simulation Animation Frequency response CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA

On digital signal processing understanding through simulation and animation tools

JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL ROGERIO ADRIAN ENRIQUEZ CALDERA (2008)

This paper describes the use of simulation and animation tools based on MathCAD, aimed to support the understanding of basic principles of digital filters. An important feature is the interaction student-computer to simulate different problems with parameter changes and its instantaneous evaluation by the software, which motivates the reasoning and understanding of the mathematical concepts by the student. In addition, the animation options in MathCAD allow the students to create virtual environments which resemble the real instrumentation procedures in the laboratory, such as the typical frequency sweep based on a signal generator and the oscilloscope. A collection of different study cases in the area of digital signal processing such as filter design, Nyquist criterium, digital filtering in the time domain by difference equations, relation to frequency response in both, continuous and discrete domains, and modulation, is described.

Article

Digital signal processing Digital filters Simulation Animation Frequency response CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA MATEMÁTICAS CIENCIA DE LOS ORDENADORES

A LabVIEW-based autonomous vehicle navigation system using robot vision and fuzzy control

JUAN MANUEL RAMIREZ CORTES Jorge Martinez Carballido María del Pilar Gómez Gil (2011)

This paper describes a navigation system for an autonomous vehicle using machine vision techniques applied to real-time captured images of the track, for academic purposes. The experiment consists of the automatic navigation of a remote control car through a closed circuit. Computer vision techniques are used for the sensing of the environment through a wireless camera. The received images are captured into the computer through the acquisition card NI USB-6009, and processed in a system developed under the LabVIEW platform, taking advantage of the toolkit for acquisition and image processing. Fuzzy logic control techniques are incorporated for the intermediate control decisions required during the car navigation. An e cient approach based on logic machine-states is used as an optimal method to implement the changes required by the fuzzy logic control. Results and concluding remarks are presented.

Article

Fuzzy Control Robot Vision Autonomous Navigation CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

Shape-based hand recognition approach using the morphological pattern spectrum

JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL GABRIEL SANCHEZ PEREZ (2009)

We propose the use of the morphological pattern spectrum, or pecstrum, as the base of a biometric shape-based hand recognition system. The system receives an image of the right hand of a subject in an unconstrained pose, which is captured with a commercial flatbed scanner. According to pecstrum property of invariance to translation and rotation, the system does not require the use of pegs for a fixed hand position, which simplifies the image acquisition process. This novel feature-extraction method is tested using a Euclidean distance classifier for identification and verification cases, obtaining 97% correct identification, and an equal error rate (EER) of 0.0285 (2.85%) for the verification mode. The obtained results indicate that the pattern spectrum represents a good featureextraction alternative for low- and medium-level hand-shape-based biometric applications.

Article

CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA MATEMÁTICAS CIENCIA DE LOS ORDENADORES

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

MARIA DEL PILAR GOMEZ GIL ANGEL MARIO GARCIA PEDRERO JUAN MANUEL RAMIREZ CORTES (2010)

Even though it is known that chaotic time series cannot be accurately predicted, there is a need to forecast their behavior in may decision processes. Therefore several non-linear prediction strategies have been developed, many of them based on soft computing. In this chapter we present a new neural network architecutre, called Hybrid and based-on-Wavelet-Reconstructions Network (HWRN), which is able to perform recursive long-term prediction over highly dynamic and chaotic time series. HWRN is based on recurrent neural networks embedded in a two-layer neural structure, using as a learning aid, signals generated by wavelets coefficients obtained from the training time series. In the results reported here, HWRN was able to predict better than a feed-forward neural network and that a fully-connected, recurrent neural network with similar number of nodes. Using the benchmark known as NN5, which contains chaotic time series, HWRN obtained in average a SMAPE = 26% compared to a SMAPE = 61% obtained by a fully-connected recurrent neural network and a SMAPE = 49% obtained by a feed forward network.

Article

CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA ELECTRÓNICA

Shape-based hand recognition approach using the morphological pattern spectrum

JUAN MANUEL RAMIREZ CORTES MARIA DEL PILAR GOMEZ GIL GABRIEL SANCHEZ PEREZ (2009)

We propose the use of the morphological pattern spectrum, or pecstrum, as the base of a biometric shape-based hand recognition system. The system receives an image of the right hand of a subject in an unconstrained pose, which is captured with a commercial flatbed scanner. According to pecstrum property of invariance to translation and rotation, the system does not require the use of pegs for a fixed hand position, which simplifies the image acquisition process. This novel feature-extraction method is tested using a Euclidean distance classifier for identification and verification cases, obtaining 97% correct identification, and an equal error rate (EER) of 0.0285 (2.85%) for the verification mode. The obtained results indicate that the pattern spectrum represents a good featureextraction alternative for low- and medium-level hand-shape-based biometric applications.

Article

CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA FÍSICA ELECTRÓNICA

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

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