Classification Techniques for Computer Vision Based Fruit Quality Inspection: A Review

This paper presents the recent developments of image processing and machine vision system in an automated fruit quality measurement system. In agricultural sector the efficiency and the accurate grading process is very essential to increase the productivity of produce. Everyday high quality fruits are exported to other countries and generate a good income. That is why the grading process of the fruit is important to improve the quality of fruits. However, fruit grading by humans in agricultural industry is not sufficient, requires large number of labors and causes human errors. Automatic grading system not only speeds up the process but also gives accurate results. Therefore, there is a need for an efficient fruits grading or classification methods to be developed. Fruit’s Color, size, weight, component texture, ripeness are important features for accurate classification and sorting of fruits such as oranges, apples, mangoes etc. Objective of this paper is to emphasize on recent work reported on an automatic fruit quality detection system. This paper presents the overview of image processing techniques for feature extraction and classification for fruit quality measurement system. Keywords—Image processing, computer vision, histogram, artificial neural network, fuzzy logic, support vector