Abstract
In this paper illustrates the improvement of a low cost machine vision system using webcams and image processing algorithms for defect detection and sorting of tomatoes The sortin g decision was based on three features extracted by the different image processing algorithms. This methodology based on the color fea tures, which used for detecting the BER from good t omatoes. Two methods were developed for decision based sorting. The color ima ge threshold method with shape factor was found eff icient for differentiating good and defective tomatoes. The overall accuracy of def ect detection attained was 94 and 96.5% respectivel y. Comparison of the results is also presented in this paper.
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