关键词: 机器视觉, 苹果分级, 逐像素遍历法, 支持向量机, 特征提取, 在线检测

Abstract: At present, the automation grading level of apple was lower. A set of apple intelligent online inspection grading system was designed to achieve an automatic, fast and accurate grading of apple quality. Taking the Hanfu apple as test object, this paper studied on apple grading by machine vision technology. The positive image of apple was divided by threshold segmentation method, and the external contour of apple was extracted by the pixel-by-pixel traversal method. The apple size feature was extracted by calculating the distance from each point to the center of gravity. At the same time, fruit shape features was extracted by calculating the ratio between apple transverse and longitudinal diameters. The support vector machine (SVM) method was used to separate the apples from both sides. Apple color characteristics were extracted by calculating the proportion of red pixels accounted for entire apple pixels, and the defective part was extracted by Fisher statistics. In this study, the hardware of the whole grading system and function of the software was realized. 400 apple samples were graded using this system, and the results showed that the total grading accuracy rate by this system was 95%. The design of this apple intelligent online inspection and grading system based on machine vision overcomed the shortcomings of traditional grading methods, accelerated the automatic degree of quality grading, and was of important significance in the field of studying fruit quality grading.

Key words: machine vision, apple grading, pixel-by-pixel traversal method, SVM, feature extraction, on-line detection