While there has been a massive increase in research into face recognition, it remains challenging problem due to conditions present real life. This paper focuses on the inherently issue of partial occlusion distortions recognition applications. We propose an approach tackle this problem. First, images are divided multiple patches before local descriptors Local Binary Patterns and Histograms Ori...

Compressed sensing (CS) sampling is a sampling method which is based on the signal sparse. Much information can be extracted from as little as possible of the data by applying CS, and this method is the idea of great theoretical and applied prospects. In the framework of compressed sensing theory, the sampling rate is no longer decided in the bandwidth of the signal, but it depends on the struc...

In this paper we propose an algorithm for image fingerprint extraction based on random selection of circular bubbles on the considered image. In more detail, a fingerprint vector is associated to the image, the components of which are the variances of pixel luminance values in randomly selected circular zones of the image. The positions and radius of these bubbles result from a random selection...

This paper presents a method for the extraction of blood vessels from fundus images. The proposed method is an unsupervised learning method which can automatically segment retinal blood vessels based on an adaptive random sampling algorithm. This algorithm consists in taking an adequate number of random samples in fundus images, and all the samples are contracted to the position of the blood ve...