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An Improved Algorithm Based on the GVF-Snake for Effective Concavity Edge Detection
College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
- 1 College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
- 2 College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
- 3 College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
- 4 College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao, China
Journal of Software Engineering and Applications·Volume 06 (2013)·Pages 174–178·Published 25 April 2013·DOI10.4236/jsea.2013.64022
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Abstract
Image segmentation is an important research area in Computer Vision and the GVF-snake is an effective segmentation algorithm presented in recent years. Traditional GVF-snake algorithm has a large capture range and can deal with boundary concavities. However, when interesting object has deep concavities, traditional GVF-snake algorithm can’t converge to true boundaries exactly. In this paper, a novel improved scheme was proposed based on the GVF-snake. The central idea is introduce dynamic balloon force and tangential force to strengthen the static GVF force. Experimen tal results of synthetic image and real image all demonstrated that the improved algorithm can capture boundary con cavities better and detect complex edges more accurately.
KeywordsImage Segmentationthe GVF-SnakeBoundary ConcavitiesBalloon ForceTangential Force
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