中国光学, 2019, 12 (6): 1329, 网络出版: 2020-01-19
数字图像相关中的散斑区域自动提取研究
Automatic extraction of speckle area in digital image correlation
数字图像相关 散斑 二阶梯度熵 自适应阈值 digital image correlation speckle second-order gradient entropy adaptive threshold
摘要
数字图像相关测量中, 相关计算前会人工选取散斑区域进行区域限定。随着工业自动化的发展, 面对散斑区域形状越来越复杂以及大量散斑图片的测量需求, 找到一种散斑区域自动提取方法至关重要。本文根据散斑的特征, 对比多种常规边缘检测方法, 提出了一种基于二阶梯度熵函数的散斑区域自动提取判定函数, 并通过分析不同的散斑图片, 确定了最佳子区熵尺寸区间以及在不同散斑图中的自适应阈值区间, 最终通过连通区域分割完成对散斑区域的自动提取。文中采用实际拍摄的散斑图对该方法进行验证, 实验结果表明: 子区熵尺寸取10 pixel以上, 该算法对散斑区域表现敏感; 自适应阈值取图中最大梯度熵值的Q-1.25至Q范围内时, 可以将散斑区域与背景区域有效分割。基本能完成对散斑区域的自动提取, 达到了相关计算前散斑区域选择的目的。
Abstract
In digital image correlation measurements, the speckle area is manually selected before the correlation calculation is performed to define the matching area. With the development of industrial automation, facing the complex shape of the speckle area and the need to measure a large number of speckle images, it is crucial to find an automatic area extraction method. According to the characteristics of speckles and by comparing various conventional edge detection methods, a decision function based on second-order gradient entropy is proposed for automatically detecting speckle regions in images. By analyzing different speckle images, the optimal sub-region entropy size interval and the adaptive threshold interval in different speckle patterns were determined and the automatic extraction of the speckle region were completed by using connected region segmentation. The method was verified by using the actual speckle pattern. The experimental results show that when the entropy size of the subregion is more than 10 pixel, the decision function is sensitive to the speckle area. When the adaptive threshold value is within the range of Q-1.25 to Q, the speckle area and the background area can be effectively separated. The automatic extraction of a speckle area can be completed and the selection of speckle area before correlation calculation is achieved.
胡慧然, 但西佐, 赵琪涵, 孙方圆, 王永红. 数字图像相关中的散斑区域自动提取研究[J]. 中国光学, 2019, 12(6): 1329. HU Hui-ran, DAN Xi-zuo, ZHAO Qi-han, SUN Fang-yuan, WANG Yong-hong. Automatic extraction of speckle area in digital image correlation[J]. Chinese Optics, 2019, 12(6): 1329.