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IEEE Transactions on Neural Networks
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In this paper we investigate the potential of performing face recognition in JPEG and JPEG2000 compressed domain. This is achieved by avoiding full decompression and using transform coefficients as input to face recognition algorithms. We propose a new comparison methodology and by employing it show that face recognition can efficiently be implemented directly into compressed domain. In the first part of our experiment we use all the available transform coefficients and show that recognition rates are comparable and in some cases even higher than recognition rates obtained by using pixels from uncompressed images (standard face recognition approach). In the second part, we propose an effective coefficient preselection method (applicable both in JPEG and JPEG2000 compressed domain). Our results show that by using the proposed method, recognition rates can be significantly improved while additionally reducing computational time. Finally, we propose what a hypothetical compressed domain face recognition system should look like.