[1] Zhang Guobao, Liu Quan,. Robust edge detection based on stationary wavelet transform [J]. Journal of Southeast University (English Edition), 2006, 22 (2): 218-221. [doi:10.3969/j.issn.1003-7985.2006.02.016]

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Robust edge detection based on stationary wavelet transform()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

22

Issue:

2006 2

Page:

218-221

Research Field:

Electromagnetic Field and Microwave Technology

Publishing date:

2006-06-30

Info

Title:

Robust edge detection based on stationary wavelet transform

Author(s):

Zhang Guobao;  Liu Quan

Research Institute of Automation, Southeast University, Nanjing 210096, China

Keywords:

edge detection;  stationary wavelet;  multiscale analysis;  fuzzy c-means

PACS:

TN957

DOI:

10.3969/j.issn.1003-7985.2006.02.016

Abstract:

By combining multiscale stationary wavelet analysis with fuzzy c-means, a robust edge detection algorithm is presented. Based on the translation invariance built in multiscale stationary wavelet transform, components in different transformed sub-images corresponding to a pixel are employed to form a feature vector of the pixel. All the feature vectors are classified with unsupervised fuzzy c-means to segment the image, and then the edge pixels are checked out by the Canny detector. A series of images contaminated with different intensive Gaussian noises are used to test the novel algorithm. Experiments show that fairly precise edges can be checked out robustly from those images with fairly intensive noise by the proposed algorithm.

References:

[1] Mallat S, Zhong S.Characterization of signals from multiscale edges [J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(7):679-698.
[2] Mallat S.A wavelet tour of signal processing [M].Beijing:China Machine Press, 2002.
[3] Canny J.A computational approach to edge detection [J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(1):679-698.
[4] User M.Texture classification and segmentation using wavelet frames [J].IEEE Transactions on Image Processing, 1995, 4(1):1596-1560.
[5] Chumsamrong W, Thitimajshima P, Rangsansert Y.Synthetic aperture radar(SAR)image segmentation using a new modified fuzzy c-means algorithm [J]. Geoscience and Remote Sensing Symposium, 2000, 2(2):624-626.
[6] Gonzalez R C, Woods R E, Eddins S L.Digital image processing using Matlab [M].Beijing:Publishing House of Electronics Industry, 2004.

Memo

Memo:

Biography: Zhang Guobao(1965—), male, doctor, associate professor, guobaozh@seu.edu.cn.

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