Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Orthogonal Transforms for Digital Signal Processing
Orthogonal Transforms for Digital Signal Processing
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This paper deals with real-time image and signal recognition based on the discrete Fourier preprocessing transform(DFPT's). The methods proposed drastically decrease the time of computation and cost of implementation while they also increase the quality of recognition in the presence of noise. Both software and hardware issues for the real-time implementation of the recognition tasks are handled with the DFPT methods.DFPT is a very simple transform, whose matrix elements consists only of combinations of ±1, 0, ±j, and/or powers of √2 (powers of 2 only are possible if so required). It is the preprocessing part of the discrete Fourier transform (DFT) in the two-stage representation of DFT.DFPT is mainly utilized for the purpose of feature extraction followed by a classification algorithm. In all the experiments carried out so far in shape recognition, signal recognition and image recognition, DFPT performed better than DFT in terms of classification accuracy. Since its computation involves only elementary operations, it is much simpler, and thereby considerably faster and easier to implement in VLSI and electro-optical architectures as well as in microprocessors than DFT.