Artificial neural network-based segmentation and apple grading by machine vision

Abstract

In this paper, a computer vision based system is introduced to automatically sort apple fruits. An artificial neural network segments the defected regions on fruit by pixel-wise processing. Statistical features are extracted from the defected regions and then fruit is graded by a supervised classifier. Linear discriminant, nearest neighbor, fuzzy nearest neighbor, adaboost and support vector machines classifiers are tested for fruit grading, where the last two are found to perform best with 90 % recognition.