图像边缘检测的多尺度Gap统计方法  

Gap Statistic Based Multi-scale Images Edge Detection Method

作　　者：黄陈蓉[1] 张正军[1] 吴慧中[1] 

机构地区：[1]南京理工大学计算机科学与技术系

出　　处：《计算机辅助设计与图形学学报》2005年第6期1268-1272,共5页Journal of Computer-Aided Design & Computer Graphics

基　　金：高等学校博士学科点专项科研基金(20020288024)

摘　　要：基于Tibshirani等的“GapStatistic”思想,利用样本灰度数据分布差分析了图像分布间隙的规律,并在讨论随机含义下屋脊边缘和阶跃边缘等概念的基础上,建立了图像边缘检测的多尺度随机模型,给出了图像边缘检测算法.最后通过实例验证了该模型的抗噪声与多尺度特性.A new concept called image distribution gap is defined and analyzed in this paper using the difference of gray-level sample distribution, which is originated from the “Gap Statistic” proposed by Tibshirani, et al. After discussing the detection for step and roof edges in random respectively, a multi-scale image edge detection random model and the corresponding algorithm are proposed. Experimental results demonstrated the good anti-noise and multi-scale properties.

关 键 词：GAP统计 多尺度 边缘检测 图像处理 模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]