Environment-Adaptive Image Segmentation Using Color Invariants

Jang Seok-Woo

KJC Korea
Journal Central

Journal of The Korea Society of Computer and Information 2021 KCI Impact Factor : 0.62

Korean | English

pISSN : 1598-849X / eISSN : 2383-9945

http://journal.kci.go.kr/jksci

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Environment-Adaptive Image Segmentation Using Color Invariants

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2010, 15(10), pp.71-78

Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Jang Seok-Woo ¹

¹안양대학교

ABSTRACT
열림/닫힘 버튼

Even though various types of image segmentation methods have been extensively introduced, robustly segmenting images to environmental conditions such as illumination changes, shading, highlight, etc, has been known to be a very difficult task. To resolve the problem in some degree, we propose in this paper an environment-adaptive image segmentation approach using color invariants. The suggested method first introduces several color invariants like W, C, U, N, and H, and automatically measures environmental conditions in which images are captured. It then chooses the most adequate color invariant to environmental factors, and effectively extracts edges using the selected invariant. Experimental results show that the proposed method can robustly perform edge-based segmentation rather than existing methods. We expect that our method will be useful in many real applications which require edge-based image segmentation.
KEYWORDS
열림/닫힘 버튼

칼라 불변량(Color invariant), 영상 분할(Image segmentation), 주변 환경(Surrounding environment), 에지(Edge)

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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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