Detection of Good Quality Front Face from Low Resolution Surveillance Camera

Abstract: The face is one of the important remote biometrics and it is used in facial analysis systems, like human-computer interaction, face detection and recognition and so on. Giving poor quality images and low resolution from inexpensive videos sequences they may give error nous and unstable results so we need a proper mechanism to deal with this problem on low resolution front face images. The approach which I have mentioned in this paper exactly deals with .To deal with this approach we need to apply the reconstruction based techniques. This algorithm has mainly two problem one is that it requires a similar images and another its improvement factor limited only two. To resolve the first problem we introduce an approach of three-step, which produces a sequence of faces which consists of similar front faces having maximum possible quality. To resolve the problem of improvement factor limitation we applied super-resolution which is based on learning based algorithm to the result of the reconstruction-based technique to enhance the quality of images. Because of this technique the improvement factor gets improved by four for whole system. Face recognition is a biometric system used to identify or verify a person from a digital image. Face Recognition system is used in security. Face recognition system should be able to automatically detect a face in an image. This involves extracts its features and then recognize it, regardless of lighting, expression, illumination, ageing, transformations (translate, rotate and scale image) and pose, which is a difficult task.

Keywords: Face-log generation, Face quality assessment, Super-resolution, surveillance video.