Active Contour Method with Separate Global Translation and Local Deformation

Authors:
Linlin Zhu;Baojie Fan;Yandong Tang
Affiliations:
Robotics Lab, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China 110016 and Graduate School of the Chinese Academy of Science, Beijing, China 100039;Robotics Lab, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China 110016 and Graduate School of the Chinese Academy of Science, Beijing, China 100039;Robotics Lab, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China 110016
Venue:
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
Year:
2009

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Abstract

Active Contour can describe targets accurately and has been widely used in image segmentation and target tracking. Its main drawback is huge computation that is still not well resolved. In this paper, by analyzing curve gradient flow, the evolution of active contour is divided into two steps: global translation and local deformation. When the curve is far away from the object, the curve just does the translation motion. This method can optimize the curve evolving path and efficiency, and then the computation cost is largely reduced. Our experiments show that our method can segment and track object effectively.