KERNEL FITTING FOR IMAGE SEGMENTATION

摘要：

Previously, a classifier called Kernel-based Nonlinear Representor (KNR) was proposed for pattern classification. In this paper KNR is changed to curve fitting for image segmentation applications. For each gray level, a curve is estimated by KNR and separated from that of a higher gray level by a threshold obtained from Newman-Pearson criterion. The thresholds are then merged into a few representative ones, with an ideal high-pass filtering approach, for image segmentation. Feasibility of the presented method in image segmentation is illustrated by some experimental results.

关键词： Image segmentation Kernel method Kernel-based nonlinear representor (KNR) Curve fitting Thresholding

作者: BEN-YONG LIU WEN-YUE WU XIAO-WEI CHEN

作者单位: Department of Computer Science, Guizhou University, Guiyang 550025, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2914-2917

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）