Luis Nino-de-Rivera

Wavelet Transform Fuzzy Algorithms for Dermoscopic Image Segmentation

This paper presents a novel approach to segmentation of dermoscopic images based on wavelet transform where the approximation coefficients have been shown to be efficient in segmentation. The three novel frameworks proposed in this paper, W-FCM, W-CPSFCM, and WK-Means, have been employed in segmentation using ROC curve analysis to demonstrate sufficiently good results. The novel W-CPSFCM algorithm permits the detection of a number of clusters in automatic mode without the intervention of a specialist.

A Modular Analog NLMS Structure for Adaptive Filtering

This paper proposes a modular Analog Adaptive filter (AAF) algorithm, in which the coefficient adaptation is carried out by using a time varying step size analog normalized LMS (NLMS) algorithm, which is implemented as an external analog structure. The proposed time varying step size is estimated by using the first element of the crosscorrelation vector between the output error and reference signal, and the first element of the crosscorrelation vector between the output error and the adaptive filter output signal, respectively. Proposed algorithm reduces distortion when additive noise power increases or DC offsets are present, without significatively decreasing the convergence rate nor increasing the complexity of the conventional NLMS algorithms. Simulation results show that proposed algorithm improves the performance of AAF when DC offsets are present. The proposed VLSI structure for the time varying step size normalized NLMS algorithm has, potentially, a very small size and faster convergence rates than its digital counterparts. It is suitable for general purpose applications or oriented filtering solution such as echo cancellation and equalization in cellular telephony in which high performance, low power consumption, fast convergence rates and small size adaptive digital filters (ADF) are required. The convergence performance of analog adaptive filters using integrators like first order low pass filter is analyzed.

Real-time processing scheme based on RM estimators

In this paper we present the capability and real-time processing features of Median M-type KNN and Wilcoxon M-type KNN filters for the removal of impulsive noise in real-time image processing applications. Extensive simulation results in known reference images have demonstrated that the proposed filter consistently could outperform other nonlinear filters by balancing the tradeoff between noise suppression and detail preservation. The criterions used to compare performance were the PSNR and MAE. The real-time implementation of image filtering was realized in the DSP TMS320C6701. The processing time of proposed filters includes the duration of data acquisition, processing and store data. We found that the values of processing time of proposed filters depend of the image to process and do not practically vary for different noise level; these values depend also of the complex calculation of influence functions and parameters of the proposed filters and the influence functions. We simulated impulsive corrupted image sequences to demonstrate that the proposed methods potentially could provide a real-time solution to quality TV/Video Transmission.

Study of the Effect of Distance and Misalignment between Magnetically Coupled Coils for Wireless Power Transfer in Intraocular Pressure Measurement

An analysis of the effect of distance and alignment between two magnetically coupled coils for wireless power transfer in intraocular pressure measurement is presented. For measurement purposes, a system was fabricated consisting of an external device, which is a Maxwell-Wien bridge circuit variation, in charge of transferring energy to a biomedical implant and reading data from it. The biomedical implant is an RLC tank circuit, encapsulated by a polyimide coating. Power transfer was done by magnetic induction coupling method, by placing one of the inductors of the Maxwell-Wien bridge circuit and the inductor of the implant in close proximity. The Maxwell-Wien bridge circuit was biased with a 10 MHz sinusoidal signal. The analysis presented in this paper proves that wireless transmission of power for intraocular pressure measurement is feasible with the measurement system proposed. In order to have a proper inductive coupling link, special care must be taken when placing the two coils in proximity to avoid misalignment between them.

Waveform generator system to transcorneal stimulation based on a digital adaptive model

The present work proposes an electronic waveform generator for transcorneal electrical stimulation (TES). The applied waveform model is generated into a digital processor by means of an adaptive finite impulse response (FIR) filter, which output waveform is synthesized from the original one registered using a multi-focal electroretinograph (MF-ERG). The stimulation waveform applied in patients with central retinal artery occlusion (CRAO) in this procedure, is qualitatively different from the one reported by others like Tano et. al. [1, 2]. Results show that CRAO patients stimulated with the proposed waveform, reported phosphenes associated with variations of the filter coefficients.

Fuzzy Filtering Method for Color Videos Corrupted by Additive Noise

A novel method for the denoising of color videos corrupted by additive noise is presented in this paper. The proposed technique consists of three principal filtering steps: spatial, spatiotemporal, and spatial postprocessing. In contrast to other state-of-the-art algorithms, during the first spatial step, the eight gradient values in different directions for pixels located in the vicinity of a central pixel as well as the R, G, and B channel correlation between the analogous pixels in different color bands are taken into account. These gradient values give the information about the level of contamination then the designed fuzzy rules are used to preserve the image features (textures, edges, sharpness, chromatic properties, etc.). In the second step, two neighboring video frames are processed together. Possible local motions between neighboring frames are estimated using block matching procedure in eight directions to perform interframe filtering. In the final step, the edges and smoothed regions in a current frame are distinguished for final postprocessing filtering. Numerous simulation results confirm that this novel 3D fuzzy method performs better than other state-of-the-art techniques in terms of objective criteria (PSNR, MAE, NCD, and SSIM) as well as subjective perception via the human vision system in the different color videos.

Portable transcorneal electrical stimulator system, applied on electrotherapy for low vision patients

The present work proposes a portable electronic waveform generator for transcorneal electrical stimulation (TES). The waveform model is generated into a digital processor, and is based on a healthy eyes multi-focal electroretinogram (MF-ERG) response. The stimulation protocol proposed in this paper is qualitatively different from the one reported by others like Inomata et. al. [1, 2]. Results show an improvement in patients visual acuity and increased electrical B wave response in standard electroretinogram (ERG) tests, when TES is applied in patients suffering low vision (LV) produced by central retinal artery occlusion (CRAO).

3D color video conversion from 2D video sequence using stereo matching technique

In this work, we present novel algorithm that permits converting 2D video color sequence into 3D one via the region based stereo matching in order to obtain the depth maps from video sequence. These depth maps were applied to design 3D video being observed via an anaglyph in a cheaper way. The anaglyphs were designed by manipulation with red component gathering two neighbor 2D frames of the video sequence. Numerous simulation results with different video sequences have confirmed good visual performance of restored 3D color video sequences by proposed framework.

Real time high frequency spectrum analyzer

This paper proposes an analog VLSI system structure to estimate real time power spectrum signals. The propose structure is base in a continuous adaptive filter where coefficients are adapted by the least mean square analog LMS algorithm. The system function to be synthesized is represented by the classical Fourier series, where the coefficients are adapted independently by analog LMS structure that can be implemented in VLSI technology. Since adaptation is carried out in continuous time, real time computing speed in high frequency spectrum estimation is an important advantage in relation to conventional Discrete Fourier Transform, and even Fast Fourier Transform applications.

A modular analog NLMS structure for system identification

Adaptive filters have been mainly developed in a digital way which may involve, in some applications, a large number of computations for filtering and adaptation. This fact may restrict the use of adaptive filters in some applications like channel equalization in cellular systems in which high performance, fast convergence rates and small size ADF are required. This paper proposes an analog adaptive filter algorithm in which the filter adaptation is carried out by using a normalized analog LMS algorithm. Proposed structure has, potentially, a very small size and faster convergence rates than its digital counterparts. This fact makes it suitable for several applications such as equalization and echo cancellation in cellular telephones in which high performance with low power consumption systems are required.