Isolating Healthy Bananas from Unhealthy Ones Based on Feature Extraction and Clustering Method Using Neural Network

Abstract

Due to the high sorting speed required during inspection and classification in packing lines, most of the current automatic systems, based on machine vision, are used. Fruit industries are not excluded about this fact. In this paper a method is proposed for detection healthy bananas and defective one. Our algorithm has 4 steps.

First, we eliminated background using segmentation methods such as FCM, HCM, Kmeans. Then we extracted the boundaries of a sample banana using edge detection approach. After that, feature from surface of a sample was extracted. Finally, by using a neural network, healthy bananas and defective one was detected.