3-level Techniques
image recognition
stationary wavelet
transform
wavelet transform
feature extraction.
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Image recognition is one of the most important applications of
information processing, in this paper; a comparison between
3-level techniques based image recognition has been
achieved, using discrete wavelet (DWT) and stationary
wavelet transforms (SWT), stationary-stationary-stationary
(sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary
(sws), stationary-wavelet-wavelet (sww), wavelet-stationary-
stationary (wss), wavelet-stationary-wavelet (wsw),
wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet
(www). A comparison between these techniques has
been implemented. according to the peak signal to noise ratio
(PSNR), root mean square error (RMSE), compression ratio
(CR) and the coding noise e (n) of each third
...
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