IMAGE ANALYSIS FOR APPLE DEFECT DETECTION

Summary. The objective of this research was to develop and test an image processing system which could identify defects on apple surfaces. A system for identifying surface defects on apples was designed, based on analyzing images acquired while apples were rotating in front of the camera. When multiple images were com-bined 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. While minimizing false positives, the classifi cation accuracy was very high. The proposed algorithm was effective in detecting various defects such as bruises, frost damage, and scab. The average classifi cation accuracy was 96 % for the samples in the experiments. Key words: apple, damage, vision system, algorithm