On Tree Detection, Counting & Post- Harvest grading of fruits Based on Image Processing and Machine Learning Approach-A Review

Abstract

—This paper reports involvement of image processing and machine vision technique to detect and count of fruits on-tree, in field condition, have been reviewed. In addition, this paper also associated with the grading of fruits in post-harvesting. Different types of algorithms are available for counting and to extract the feature of fruit characters by capturing the on-tree fruit image by any conventional RGB camera. With the help of this counting algorithm and feature extraction technique, fruit is detected and counted. This work also surveys grading method applied to the post-harvest fruits. Grading method involves: identification of mature & immature fruits, intact & diseased fruits and also predict the weight of the fruit from its shape. The grading of fruit can be done by using different types of the classifier. The main features, drawback and future prospective of previous work in this area are summarized. Keyword-On-tree detection & counting of fruits, Post-harvest grading of fruits, K-Means clustering, Histogram method, HSI technique, color-mapping, RGB color space method, SVM, KNN, ANN, Fuzzy logic.