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Proceedings Paper

Image transition region extraction and thresholding with nonlocal spatial feature
Author(s): Limin Zhang; Tao Wu; Junjie Yang
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Paper Abstract

Because of the only use of local spatial features, classical methods for transition region extraction and thresholding would result in unsatisfied, even complete failure results under the existence of noises or outliers. In view of this, we propose a novel algorithm based on nonlocal spatial feature and gray level difference. This algorithm generates the nonlocal spatial feature and gray level difference first, and constructs the effective feature matrix based on the above two features, then obtains an automatic threshold related to the effective feature matrix according to a statistical method for thresholding, meanwhile extracts the transition region. Finally, the algorithm obtains the optimal grayscale threshold by calculating the grayscale mean of transition pixels, and yields the binary result. Experimental results show that, the proposed algorithm performs good result of transition region extraction and thresholding, and it is reasonable and effective, can be as an alternative to traditional methods.

Paper Details

Date Published: 21 July 2017
PDF: 8 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042027 (21 July 2017); doi: 10.1117/12.2281680
Show Author Affiliations
Limin Zhang, Lingnan Normal Univ. (China)
Tao Wu, Lingnan Normal Univ. (China)
Junjie Yang, Lingnan Normal Univ. (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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