Fast multi-scale edge detection algorithm based on wavelet transform
The traditional edge detection algorithms have certain noise amplification, 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 extract useful information from the edge of an image. The wavelet transform is at various scales, wavelet transform of each scale provides certain edge information, so called multi-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.
wavelet transform fast multi-scale edge detection image analysis target recognition
Jie Zang Yanjun Song Shaojuan Li Guoyun Luo
Engineering Institute, Air Force Engineering University, Xi’an Shaanxi, China 710038 Science Institute, Air Force Engineering University, Xi’an Shaanxi, China 710051 93936 Armed Forces Ministry, Yinchuan Ningxia, China 750000
国际会议
桂林
英文
1-5
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）