Using Metaheuristic Algorithms for Improving Images Compression Rate and Recognition Ratio in a Face Recognition System

Images compression is an inevitable part of almost any images processing system, including face recognition systems. One of the main challenges in face recognition systems is reduction of recognition ratio due to the lossy compression of the images.In this paper, a new approach for face images compression improve is presented  by producing new quantization tables in JPEG method, using metaheuristic algorithms. The criterion for selecting the best quantization tables is the recognition rate of the compressed images. The new tables not only do not reduce the recognition rate, but also have the ability to increase the compression ratio at the same time. Experiments have been performed at different intervals of the compression ratio by adjusting the quality parameter on different sets of the FERET database. The results of the studies indicate that the recognition rate is maintained or in some cases is even increased, despite the increase in the compression rate.