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- W1479920988 abstract "AbstractImage communication is a significant research area which involves improvement in image coding and communication techniques. In this paper, Principal Component Analysis (PCA) is used for face image coding and the coded images are protected with convolutional codes for transmission over Additive White Gaussian Noise (AWGN) channel. Binary Phase Shift Keying (BPSK) is used for the modulation of digital (binarized) coded images. Received binarized coded images are first decoded by the convolutional decoder using the Viterbi algorithm and then PCA decoded for recognition of the face. Unequal error protection (UEP) with two convolutional encoders with different rates is used to increase the overall performance of the system. The recognition rate of the transmitted coded face images without any protection is 35%, while equal protection with convolutional codes gives rates up to 85% accuracy. On the other hand, the proposed UEP scheme provides recognition rates up to 95% with reduced redundancy.KeywordsFace RecognitionRecognition RateFace ImageConvolutional CodeViterbi AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1479920988 date "2005-01-01" @default.
- W1479920988 modified "2023-09-23" @default.
- W1479920988 title "Unequal Error Protection Using Convolutional Codes for PCA-Coded Images" @default.
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- W1479920988 doi "https://doi.org/10.1007/11559573_42" @default.
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