J4

• 计算机科学 • 上一篇    下一篇

基于统计的显微图像边缘检测阈值分析方法

罗宏文1, 马驷良1, 徐中宇12   

  1. 1. 吉林大学 数学研究所, 长春 130012; 2. 长春工业大学 计算机科学与工程学院, 长春 130012
  • 收稿日期:2005-05-20 修回日期:1900-01-01 出版日期:2006-05-26 发布日期:2006-05-26
  • 通讯作者: 马驷良

Threshold Analysis of Micro Image in Edge DetectionBased on Statistical Approach

LUO Hong-wen1, MA Si-liang1, XU Zhong-yu1,2   

  1. 1. Institute of Mathematics, Jilin University, Changchun 130012, China; 2. College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China
  • Received:2005-05-20 Revised:1900-01-01 Online:2006-05-26 Published:2006-05-26
  • Contact: MA Si-liang

摘要: 针对复杂噪音干扰的显微图像, 提出一种新的基于统计原理的边缘检测阈值分析方法. 应用统计函数提取图像中梯度大的一个区域, 再由非极值抑制算法提取边缘像素. 在选择阈值前, 对每一像素的梯度值进行局部标准化, 去除模糊和全局阈值选择的不合适性. 所做分析的统计特性使得输入参数的选择对噪音图像具有鲁棒性, 能有效处理图像中的随机噪音. 实验结果表明, 所提出的算法具有稳定性强、 鲁棒性好的 特性.

关键词: 显微图像, 边缘检测, 统计阈值, 非极值抑制

Abstract: An edge detection method of noisy micro image was proposed where threshold was performed via statistical principles. The region whose change rate of intensity is maximum was extracted by applying statistical functions. Then an edge pixel was detected from the extracted region with the nonmaxima suppression algorithm. The gradient strength at each pixel was standardized locally before threshold was selected so as toeliminate the ambiguity and inappropriateness in choosing global threshold values. However, the values of the input parameters providing the appreciable results in the proposed detector were found to be more stable than other edge detectors and possess statistical interpretation, which can efficiently handle random noise present in an image. The results of the proposed algorithm were compared with those of many wellknown edge detectors. The results suggest it can produce reliable, robust, and smooth edges.

Key words: micro image, edge detection, statistical threshold, non-maxima suppression

中图分类号: 

  • TP391.41