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8 December 2011 Fast multi-scale edge detection algorithm based on wavelet transform
Jie Zang, Yanjun Song, Shaojuan Li, Guoyun Luo
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Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 80030F (2011) https://doi.org/10.1117/12.898802
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
The traditional edge detection algorithms have certain noise amplificat ion, making there is a big error, so the edge detection ability is limited. In analysis of the low-frequency signal of image, wavelet analysis theory can reduce the time resolution; under high time resolution for high-frequency signal of the image, it can be concerned about the transient characteristics of the signal to reduce the frequency resolution. Because of the self-adaptive for signal, the wavelet transform can ext ract useful informat ion from the edge of an image. The wavelet transform is at various scales, wavelet transform of each scale provides certain edge informat ion, so called mult i-scale edge detection. Multi-scale edge detection is that the original signal is first polished at different scales, and then detects the mutation of the original signal by the first or second derivative of the polished signal, and the mutations are edges. The edge detection is equivalent to signal detection in different frequency bands after wavelet decomposition. This article is use of this algorithm which takes into account both details and profile of image to detect the mutation of the signal at different scales, provided necessary edge information for image analysis, target recognition and machine visual, and achieved good results.
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Jie Zang, Yanjun Song, Shaojuan Li, and Guoyun Luo "Fast multi-scale edge detection algorithm based on wavelet transform", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030F (8 December 2011); https://doi.org/10.1117/12.898802
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KEYWORDS
Edge detection
Wavelet transforms
Signal detection
Detection and tracking algorithms
Image analysis
Detection theory
Wavelets
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