Face recognition with positive and negative samples using support vector machine
A.D. Chitra, P. Ponmuthuramalingam · ACCENTS Transactions on Image Processing and Computer Vision · 2016
IntroductionIn computer science, it also covers many different sub-areas such as face detection, face tracking, feature extraction, etc.These feature values depended on the detection of geometric facial features, including the distance and angles between points such as eye corners, mouth extremities, nostrils and chin top.Digital image processing is concerned with the development of computer algorithms working on digitized images [1].Digital Image Processing concerns the following field of sciences viz pattern recognition, optics, signal processing, electronics, cognitive science and perception science.The goal of image processing is usually automatic detection or recognition of image content, in which case one can speak of machine vision [2].This pipeline consists of the steps of pre-processing, feature extraction, segmentation, object recognition and image understanding [3].In each step, the input and output data could either be images (pixels), measurements in images (features), and decisions made in previous stages of the chain (labels) or even object relation information (graphs) [4].