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This paper proposes a biometric system to identify people using common biomedical sensors. A dataset is built by groups of signals acquired from 25 people, and is used in the system. The present proposal applies a combination of principal components analysis and support vector machines to identify people by a group of biometric signals: electrocardiogram, airflow, temperature, pulse oximetry, electromyogram...
In this paper, the proposed implementation of a soft-biometric system for automatic age detection from facial images is described. In order to do this, the method followed was that of a classical biometric system. The first step is preprocessing, to enhance the feature extraction. The next step is the parameterization, where techniques like wavelet transformed, discrete cosine transformed or local...
The paper presents a unique combination of texture feature extraction techniques which can be used in image texture analysis. Setting the prime objective of classifying different texture images, the Local Binary Pattern (LBP) and a modified form of Gray Level Run Length Matrix (GLRLM) are implemented initially. The next phase involves use of combination of the former two methods to extract improved...
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