一种区域分离方法及其在米粒检测中的应用

A Region-disconnecting Algorithm and Application to Detection of Rice Kernels

针对计算机视觉技术中米粒靠接在一起不利于大米的分级检测,采用图像处理分离靠接在一起的米粒融合区域,提出了基于扫描式区域增长的区域分离方法。该方法充分利用了单个米粒图像区域为凸性区域这一几何特点,通过区域增长的方法在图像中寻找由凸性米粒靠接在一起所形成的融合凹性区,并从凹处将融合区域分离开来。由于利用了米粒区域的几何特征来分离融合米粒区域,因此分离工作的自适应性强。大米垩白粒率的检测实验结果表明:该方法分离融合米粒区域的成功率达到了100%,而且检测结果与人工检测结果基本一致。

A region-disconnecting algorithm based on region growing with scanning is proposed ,which disconnects the merged rice kernel image regions through image processing. The algorithm uses the geometric feature of a single convex rice kernel to search the concave regions merged with rice kernels during the region growing with scanning and disconnect the regions at the concave positions in image. Because of using the geometric feature of rice kernels,the disconnection with the concave region identification is adaptive. In the experiment of detection of the percentage of chalky kernels, the algorithm was tested on 100 rice kernels with some physically-connected kernels and some chalky kernels,the merged rice kernel image regions were disconnected with the efficiency up to 100% ,and the detection result of the percentage of chalky kernels using the algorithm is the same as the manual inspection result.