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A novel immune image template set for fuzzy image segmentation and its application research

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5 Author(s)
Dongmei Fu ; Sch. of Inf. & Eng., Univ. of Sci. & Technol. Beijing, Beijing, China ; Tao Yang ; Xintao Qiu ; Riha, K.
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Image segmentation is one of the classic problems in the computer vision field. Although a lot of successful operators and algorithms have been proposed, fuzzy image segmentation does not always achieve satisfactory results. This paper is inspired by Positive Selection Algorithm and Negative Selection Algorithm and, is based on the mechanism and process where T-cell is activated by the MHC molecule. A new positive selection algorithm is introduced which establishes so-called templates set for immune detection. This algorithm is based on processing of image information represented as a gray value statistic rather than arithmetic gradient formulation. It is comprised of a template set not just a single template. Therefore it gives good results for different images. The presented algorithm is used for image segmentation into objects, background and fuzzy edge in fuzzy infrared images.

Published in:

Telecommunications and Signal Processing (TSP), 2011 34th International Conference on

Date of Conference:

18-20 Aug. 2011