A system for identifying surface defects on potatoes was designed, based on analyzing images acquired while potatoes
were rotating in front of the camera. When multiple images were combined and adjustments made for rotation, dark areas
caused by defects would appear with almost the same shape and at the same place in three or more frames. The proposed
algorithm was able to detect defects. To increase the standard mode for the system, in parallel with defect detection, a simple
size sorting is also applied. The best algorithm method in classification has an accuracy of about 95% and the size grading
section has an accuracy of about 96.86% for the samples in these experiments.