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|Title:||A transform domain face recognition approach|
|Keywords:||Discrete Cosine Transforms|
Hidden Markov Models
|Citation:||TENCON'99: Proceedings of the IEEE Region 10 Conference on Multimedia Technology for Asia-Pacific Information Infrastructure (V 1), Cheju Island, Korea, 15-17 September 1999, 104-107|
|Abstract:||The paper combines DCT (discrete cosine transform) and HMM (hidden Markov model) to realise a face recognition technique. The face images are subsampled to obtain a sequence of face sub-images. Each sub-image is DCT transformed and the coefficients are scanned (similar to the JPEG image compression method) to form a vector. These vectors are applied to HMMs for recognition. Two different face databases-ORL and SPANN are used. The recognition rate for ORL is 99.5% with 5 training and 5 testing images per subject. The SPANN database has a recognition rate of 98.75% with 3 training images and 4 test images per subject. Further, an investigation into dependence of recognition rate on number of training images, and number of HMM states.|
|Appears in Collections:||Proceedings papers|
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