基于Blob分析的红枣表面缺陷在线检测技术

搭建一个基于机器视觉的红枣表面缺陷在线检测平台,实现红枣全表面信息的自动化在线实时测量。根据红枣及其表面缺陷的特征,提出在颜色空间模型中采用Blob分析算法进行红枣与背景的分离以及红枣表面缺陷的识别,给出不同缺陷特征种类的颜色空间模型和分割阈值,快速准确地实现破头果、霉变果、浆头果、虫蛀果等典型红枣表面缺陷的识别。试验结果表明,该方法检测结果稳健可靠,缺陷果识别的准确率可达到90%以上。

Research on online detection for jujube surface defects based on blob analysis

In this paper, an online detection platform for jujube surface defects based on machine vision is designed to realize the automatic real-time measurement of full-surface information of jujubes. According to the characteristics of jujubes and their surface defects, the blob analysis algorithm in the color space was used to separate the jujubes from the background and identification of the surface defects of jujube model was proposed. The color space model and the segmentation threshold of different defect characteristics were given,the broken fruit, mold fruit, pulp head fruit, insect fruit and other typical jujubes surface defects identification was realized speedily and accurately . It shows that the results of this study are robust and reliable in this experiment, and the accuracy of defective identification is over 90%.