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Proceedings Paper

Fast multi-scale edge detection algorithm based on wavelet transform
Author(s): Jie Zang; Yanjun Song; Shaojuan Li; Guoyun Luo
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Paper 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.

Paper Details

Date Published: 8 December 2011
PDF: 5 pages
Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030F (8 December 2011); doi: 10.1117/12.898802
Show Author Affiliations
Jie Zang, Air Force Engineering Univ. (China)
Yanjun Song, Air Force Engineering Univ. (China)
Shaojuan Li, Air Force Engineering Univ. (China)
Guoyun Luo, 93936 Armed Forces Ministry (China)


Published in SPIE Proceedings Vol. 8003:
MIPPR 2011: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Nong Sang, Editor(s)

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