An Improved Object Detection and Contour Tracking Algorithm Based on Local Curvature

被引:0
|
作者
Lee, Jung-Ho [1 ]
Hua, Fang [1 ]
Jang, Jong Whan [1 ]
机构
[1] PaiChai Univ, Taejon 302735, South Korea
关键词
active contour model; snake algorithm; object detection; object contour tracking; local curvature; ACTIVE CONTOURS; SNAKES; MODEL; FLOW;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Using the classical snake algorithm it is difficult to detect the contour of an object with complex concavities. Whereas the GVF (Gradient Vector Flow) method successfully detects the concavity of a contour, but consumes lots of time to compute the energy map. In this paper, we propose a fast snake algorithm to reduce computation time and to improve the performance of detecting and tracking the contour. In order to represent the object's contour accurately, a snake point inserting and deleting strategy is also proposed. Simulation results from a sequence of images show that our method performs well in detecting and tracking the object's contour.
引用
收藏
页码:25 / +
页数:2
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