期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2015
卷号：4
期号：1
页码：10051-10056
出版社：IJECS
摘要：This paper presents a novel defect segmentation of fruits based on color features with K-means clustering algorithm. Thealgorithms Gaussian Mixture Model (GMM), Support Vector Machine (SVM) are used for background removal and color classificationrespectively. Physical recognition of defected fruit is very time overwhelming. These days, most existing fruit superiority detecting andgrading system have the drawback of low efficiency, low speed of grading, high cost and complexity. Although the color is not commonlyused for defect segmentation, it produces a high discriminative power for different regions of image. This approach thus provides a feasiblerobust solution for defect segmentation of fruits. Image processing gives solution for the automated fruit size grading to give precise,dependable, unfailing and quantitative information apart from handling large volumes, which may not be achieved by employing the humangraders. The hardware model can also be created by using PIC microcontroller. This will have a good aspect of application in fruit qualitydetecting industries
