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http://dx.doi.org/10.6109/jkiice.2010.14.8.1819

Image Segmentation Algorithm for Fish Object Extraction  

Ahn, Soo-Hong (코아로직)
Oh, Jeong-Su (부경대학교 이미지시스템공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.14, no.8, 2010 , pp. 1819-1826 More about this Journal
Abstract
This paper proposes the image segmentation algorithm to extracts a fish object from a fish image for fish image retrieval. The conventional algorithm using gray level similarity causes wrong image segmentation result in the boundary area of the object and the background with similar gray level. The proposed algorithm uses the reinforced edge and the adaptive block-based threshold for the boundary area with weak contrast and the virtual object to improve the eroded or disconnected object in the boundary area without contrast. The simulation results show that the percentage of extracting the visual-fine object from the test images is under 90% in the conventional algorithm while it is 97.7% in the proposed algorithms.
Keywords
image segment; image retrieval; fish image;
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