Extended Snake Algorithm Using Color Variance Energy (컬러 분산 에너지를 이용한 확장 스네이크 알고리즘)

Seung Tae Lee (이승태); Youngjun Han (한영준); Hernsoo Hahn (한헌수)

Extended Snake Algorithm Using Color Variance Energy

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2009, 14(10), pp.83-92
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

Seung Tae Lee ¹, Youngjun Han ¹, Hernsoo Hahn ¹

¹숭실대학교

Accredited

ABSTRACT

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 % .

KEYWORDS

매개변수 스네이크(parametric snake), 컬러 분산(color variance), 영상 분할 기법(image segmentation method), 에너지(energy), 동적 윤곽선 모델(active contour model)

Citation status

* References for papers published after 2023 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

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