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A new edge detection algorithm by combining multiscale wavelet technique and genetic fuzzy clustering algoithm is proposed in this paper (called WGFCA), which can realize edge detection of input image automatically. Based on the theory that signals and noise have different characters along wavelet decomposition scales, WGFCA firstly multiply the wavelet coefficient of input image at adjacent scales...
This paper presents a novel method for edge detection based on multiscale wavelet features and fuzzy c-means clustering. Firstly, an effective feature extraction algorithm using multiscale wavelet transform was proposed to extract classification features, thus the feature vector for each pixel was gained, which contained the gradient information in various directions; and then, these vectors were...
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