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Low frequency wavelet coefficients include much important vision information of the image, and are useful to image recognition and understanding. While at present, the applications of the low frequency wavelet coefficients are limited in the researches of image analysis. In this paper, the authors extracted the BFV (Binary Feature Vector, BFV) and TFV (Ternary Feature Vector, TFV) of low frequency wavelet coefficients based on non-parameter local transformation, which adopts the comparison results of the coefficient amplitudes in the neighborhood with the center coefficient to extract the feature rapidly.
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