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Research Article Open Access
Face recognition is one of the challenging fields and rigorous research has been carried out in this regard. Though the technique is robust in recognizing faces for authentication, it often deals with storing quite a large number of face images of the same person with variations in pose, occlusions, expressions, etc. When many subjects are taken into account, the number of samples in the training database becomes considerably high and the storage becomes cumbersome. Hence memory management becomes a bigger issue and this is often a domain on which not much fuss is laid upon. The aim of this paper is to throw light on data compression and use a few of the techniques to compress face images. 507 face images from the AR face database were used and compressed with four different algorithms. The Compression Ratio (CR) and Bits Per Pixel (BPP) were calculated. It was found that these techniques were vital for building efficient face recognition systems.