Reza R. Adhami

Stress monitoring using a distributed wireless intelligent sensor system

We are developing personal health monitors based on a wireless body area network (BAN) of intelligent sensors. Individual monitors will be integrated into a distributed wireless system for synchronized monitoring of a group of subjects. This system could be used during the selection process and as part of a psychophysiological evaluation of military members undergoing intense training. We use measures of heart-rate variability to quantify stress level prior to and during training as well as to predict stress resistance. This task requires reliable, high-precision instrumentation and synchronized measurements from a group of individuals over prolonged periods (days of training).

Classifying mammographic mass shapes using the wavelet transform modulus-maxima method

In this article, multiresolution analysis, specifically the discrete wavelet transform modulus-maxima (mod-max) method, is utilized for the extraction of mammographic mass shape features. These shape features are used in a classification system to classify masses as round, nodular, or stellate. The multiresolution shape features are compared with traditional uniresolution shape features for their class discriminating abilities. The study involved 60 digitized mammographic images. The masses were segmented manually by radiologists, prior to introduction to the classification system. The uniresolution and multiresolution shape features were calculated using the radial distance measure of the mass boundaries. The discriminating power of the shape features were analyzed via linear discriminant analysis (LDA). The classification system utilized a simple Euclidean metric to determine class membership. The system was tested using the apparent and leave-one-out test methods. The classification system when using the multiresolution and uniresolution shape features resulted in classification rates of 83% and 80% for the apparent and leave one-out test methods, respectively. In comparison, when only the uniresolution shape features were used, the classification rates were 72 and 68% for the apparent and leave-one-out test methods, respectively.

Fast and adaptive bidimensional empirical mode decomposition using order-statistics filter based envelope estimation

A novel approach for bidimensional empirical mode decomposition (BEMD) is proposed in this paper. BEMD decomposes an image into multiple hierarchical components known as bidimensional intrinsic mode functions (BIMFs). In each iteration of the process, two-dimensional (2D) interpolation is applied to a set of local maxima (minima) points to form the upper (lower) envelope. But, 2D scattered data interpolation methods cause huge computation time and other artifacts in the decomposition. This paper suggests a simple, but effective, method of envelope estimation that replaces the surface interpolation. In this method, order statistics filters are used to get the upper and lower envelopes, where filter size is derived from the data. Based on the properties of the proposed approach, it is considered as fast and adaptive BEMD (FABEMD). Simulation results demonstrate that FABEMD is not only faster and adaptive, but also outperforms the original BEMD in terms of the quality of the BIMFs.

Image Segmentation and Shape Analysis for Road-Sign Detection

This paper proposes an automatic road-sign recognition method based on image segmentation and joint transform correlation (JTC) with the integration of shape analysis. The presented system is universal, which is able to detect traffic signs of any countries with any color and any of the existing shapes (e.g., circular, rectangular, triangular, pentagonal, and octagonal) and is invariant to transformation (e.g., translation, rotation, scale, and occlusion). The main contributions of this paper are: 1) the formulation of two new criteria for analyzing different shapes using two basic geometric properties, 2) the recategorization of the rectangular signs into diamond or nondiamond shapes based on the inclination of the four sides with the ground and 3) the employment of the distortion-invariant fringe-adjusted JTC (FJTC) technique for recognition. There are three main stages in the proposed algorithm: 1) segmentation by clustering the pixels based on the color features to find the regions of interest (ROIs); 2) traffic-sign detection by using two novel shape classification criteria, i.e., the relationship between area and perimeter and the number of sides of a given shape; and 3) recognition of the road sign using FJTC to match the unknown signs with the known reference road signs stored in the database. Experimental results on real-life images show a high success rate and a very low false hit rate and demonstrate that the proposed framework is invariant to translation, rotation, scale, and partial occlusions.

Wireless personal area networks in telemedical environment

Presents a new design of a wireless personal area network with physiological sensors for medical applications in a telemedical environment. Intelligent wireless sensors perform data acquisition and limited processing. Individual sensors monitor specific physiological signals (such as EEG, EGG, GSR, etc.) and communicate with each other and the personal server. The personal server integrates information from different sensors and communicates with the rest of the telemedical system as a standard mobile unit. The authors present their prototype implementation of the wireless intelligent sensor (WISE) based on a very low power consumption microcontroller and a DSP-based personal server. In future the authors expect all components of WISE to be integrated in a single chip for use in a variety of new medical applications and sophisticated human computer interfaces.

A novel approach of fast and adaptive bidimensional empirical mode decomposition

Bidimensional empirical mode decomposition (BEMD) techniques are associated with high computation time and other artifacts because of the application of two dimensional (2D) scattered data interpolation methods. In this paper, order statistics filters are employed to get the upper and lower envelopes in the BEMD process, instead of the surface interpolation. Based on the achieved characteristics of the proposed approach, it is considered as fast and adaptive BEMD (FABEMD). Simulation results demonstrate that besides reducing the computation time, FABEMD outperforms the original BEMD in terms of the quality in some cases.

A customized Gabor filter for unsupervised color image segmentation

This paper presents work on accurate image segmentation utilizing local image characteristics. Image features are measured by employing an appropriate Gabor filter with adaptively chosen size, orientation, frequency and phase for each pixel. An image property called phase divergence is used for the selection of the appropriate filter size. Characteristic features related to the change in brightness, color, texture and position are extracted for each pixel at the selected size of the filter. In order to cluster the pixels into different regions, the joint distribution of these pixel features is modeled by a mixture of Gaussians utilizing three variants of the expectation maximization (EM) algorithm. The three different versions of EM used in this work for unsupervised clustering are: (1) penalized EM, (2) penalized stochastic EM, and (3) penalized inverse EM. Given the desired number of Gaussian mixture components, all three EM algorithms estimate the parameters of the mixture of Gaussians model that represents the joint distribution of pixel features. We determine the value of the number of models that best suits the natural number of clusters present in the image based on the Schwarz criterion, which maximizes the posterior probability of the number of groups given the samples of observation. This segmentation algorithm has been tested on the images of the Berkeley segmentation benchmark and the performance has demonstrated the effectiveness, accuracy and superiority of the proposed method.

BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION USING VARIOUS INTERPOLATION TECHNIQUES

Scattered data interpolation is an essential part of bidimensional empirical mode decomposition (BEMD) of an image. In the decomposition process, local maxima and minima of the image are extracted at each iteration and then interpolated to form the upper and the lower envelopes, respectively. The number of two-dimensional intrinsic mode functions resulting from the decomposition and their properties are highly dependent on the method of interpolation. Though a few methods of interpolation have been tested and/or applied to the BEMD process, many others remain to be tested. This paper evaluates the performance of some of the widely used surface interpolation techniques to identify one or more good choices of such methods for envelope estimation in BEMD. The interpolation techniques studied in this paper include various radial basis function interpolators and Delaunay triangulation based interpolators. The analysis is done first using a synthetic texture image and then using two different real texture images. Simulations are made to focus mainly on the effect of interpolation methods by providing less or negligible control on the other parameters or factors of the BEMD process.

A novel approach to fingerprint pore extraction

Automated fingerprint identification systems (AFIS) have become a popular tool in many security and law enforcement applications. Most of these systems rely on the matching of fingerprints using the position and orientation of ridge endings and bifurcations within the fingerprint image. While this information is sufficient for matching fingerprints in small databases, it is not discriminatory enough to provide good results on large collections of fingerprint images. This paper presents a means of obtaining additional discriminatory information from fingerprint images by demonstrating a novel method to extract the locations of sweat pores from the grayscale fingerprint image. This is achieved through the implementation of a modified minimum squared error approach. The proposed algorithm is capable of obtaining good results even from images obtained from basic 500 dpi optical live-scan devices despite the common belief that images obtained at this resolution are not of high enough quality. Results of the proposed method are demonstrated on fingerprint images taken both from a common live-scan device and the inked prints of the NIST 4 database. An explanation of the approach is presented, the results are discussed, and future research possibilities are put forth.

Arbitrary waveform DDFS utilizing Chebyshev polynomials interpolation

A new technique of arbitrary waveform direct digital frequency synthesis (DDFS) is introduced. In this method, one period of the desired periodic waveform is divided into m sections, and each section is approximated by a series of Chebyshev polynomials up to degree d. By expanding the resultant Chebyshev polynomials, a power series of degree d is produced. The coefficients of this power series are obtained by a closed-form direct formula. To reconstruct the desired signal, the coefficients of the approximated power series are placed in a small ROM, which delivers the coefficients to the inputs of a digital system. This digital system contains digital multipliers and adders to simulate the desired polynomial, as well as a phase accumulator for generating the digital time base. The output of this system is a reconstructed signal that is a good approximation of the desired waveform. The accuracy of the output signal depends on the degree of the reconstructing polynomial, the number of subsections, the wordlength of the truncated phase accumulator output, as well as the word length of the DDFS system output. The coefficients are not dependent on the sampling frequency; therefore, the proposed system is ideal for frequency sweeping. The proposed method is adopted to build a traditional DDFS to generate a sinusoidal signal. The tradeoff between the ROM capacity, number of sections, and spectral purity for an infinite output wordlength is also investigated.