摘要
全局阈值的边缘检测方法容易导致局部图像的边缘漏检,而将图像分块进行局部检测,又存在局部间阈值差异较大,导致局部边缘误检和漏检。针对此问题,本文提出一种基于图像分块的局部阈值动态选取方法:利用熵对图像分块,考虑上邻域的影响动态求解局部阈值,保证局部间阈值的连续性。将本文方法应用于Robert算子、Canny算法,结果表明可有效提高检测精度,并能增强边缘的连续性。
Most of the current edge detection methods adopt global threshold selection, which leads to the missing edge of local image. Moreover, the existing local threshold selection based on image partition causes a big difference of local thresholds and makes the edge discontinuity. Thus, in order to solve these problems, a method of local dynamic threshold selection based on im- age partition is proposed. Entropy is used to block image. The influence of the neighborhood on dynamics is considered to calcu- late the local threshold and ensure the continuity of local thresholds. Finally, the method is applied to Robert operator and Canny algorithm. The results show that the dynamic threshold selection can improve the detection accuracy effectively and enhance the continuity of edge.
出处
《计算机与现代化》
2016年第11期53-57,共5页
Computer and Modernization
基金
国家大学生创新创业训练计划项目(201510699249)
