Shape Context with Bilinear Interpolation

摘要：

Shape context is intended to be a way of describing shapes that allows for measuring shape similarity and recovering point correspondences. It is widely used in object recognition, and gets encouraging performance. But shape context is easily affected by noise points and slightly transition. In image processing, bilinear interpolation is practical and effective, allowing the resulting image appears smoother rather than jagged rendering, and more robust to slightly transition. In this paper, we use the bilinear interpolation to calculate shape context. Experimental result on 20 classes of object containing 500 images shows that robust objects matching can be achieved with our proposed method.

关键词： shape context descriptor bilinear interpolatron

作者: Bin Yan Shao-Zi Li Song-Zhi Su

作者单位: Cognitive Science,Xiamen University,Fujian,China,361005 Fujian Key lab of brain-like intelligent system,Xiamen,Fujian,China, 361005

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1282-1286

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）