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Efficient Image Segmentation Using Morphological Watershed Algorithm
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 Title & Authors
Efficient Image Segmentation Using Morphological Watershed Algorithm
Kim, Young-Woo; Lim, Jae-Young; Lee, Won-Yeol; Kim, Se-Yun; Lim, Dong-Hoon;
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This paper discusses an efficient image segmentation using morphological watershed algorithm that is robust to noise. Morphological image segmentation consists of four steps: image simplification, computation of gradient image and watershed algorithm and region merging. Conventional watershed segmentation exhibits a serious weakness for over-segmentation of images. In this paper we present a morphological edge detection methods for detecting edges under noisy condition and apply our watershed algorithm to the resulting gradient images and merge regions using Kolmogorov-Smirnov test for eliminating irrelevant regions in the resulting segmented images. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with percentage error as well as computational time needed to segment images. The proposed algorithm can efficiently improve segmentation accuracy and significantly reduce the speed of computational time.
Morphological watershed algorithm;image segmentation;morphological gradient image;region merging;Kolmogorov-Smirnov test;
 Cited by
정확한 경계 추출 및 수행시간 단축을 위한 개선된 워터쉐드 알고리즘,박동인;김태원;고윤호;최재각;

한국멀티미디어학회논문지, 2010. vol.13. 10, pp.1463-1473
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