Pattern Recognition in Compressed DCT Domain (TP-P2)

Author(s) : Daidi Zhong (Tampere University of Technology, Finland) Irek Def¨Ĥe (Tampere University of Technology, Finland)

Abstract : Images and video are currently predominantly handled in compressed form. Block-based compression standards are by far the most widespread. It is thus important to devise information processing methods operating directly in compressed domain. In this paper we investigate this possibility on the example of simple face information processing method based on the DCT (Discrete Cosine Transform) blocks. We use patterns of quantized 4x4 DCT blocks for representing local picture information. These patterns at different quantization levels provide very flexible representation of picture information. We represent global information in pictures by histograms of quantized DCT pattern distributions. The approach is tested on database of face images and it is shown that despite its simplicity provides good results in the face recognition problem.

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