Automatic detecting and grading method of potatoes based on machine vision

In order to realize grading of potato, a potato grading system based on machine vision was developed. Two pieces of plane mirror placed in V-shape were used to get three surface images of a potato at one time. Volume method based on minimum circumscribed cylinder was proposed to grade potatoes according to their size, the ratio of width and length of the longest diameter circum-rectangle was used to grade potatoes according to their shape. On the basis of characteristics of potato defects, defect area, diagonal length and cross method were used as criterions of the lacunary, dry rot, mechanical damaged, budded and misshapen potatoes. Experiments showed that the recognition accuracy of potato defects was 91.0%. The results indicate that the classification method has a high accuracy, and can be used for external quality online detection of potatoes.