A Review on Automatic Defect Detection and Granding of Single Color Fruit

Nowadays, quality evaluation of fruits is important and it plays vital role in the food and agricultural industry. The fruits in the market satisfy the consumer preferences. So, to maintain the quality, detection of a defect on fruits is necessary. Before few years this task completed by manually. But manual sorting shows inconsistency and inaccuracy in a result. This paper presents the three-dimensional color grading technique for sorting the fruits and detecting defects on it. This work having a novel defect detection of fruits based on color features with K-means clustering unsupervised algorithm. We used color images of fruits for defect detection. Defect detection in different stages. Initially, the feature extraction is performed, and then classifier is used to classify the fruits according to of their maturity level. In feature extraction, we exacted the color, edge, texture feature. Although the color is not commonly used for defect detection, it produces a high distinctions power for different regions of the image. Also, in these paper uses the automatic color grading system to determine the color quality by directly comparing fruit color against the predefined and set of reference color or by using a set of color separation parameter.