Abstract
Grading of persimmon fruits into three commercially maturity stages was conducted by image analysis technique. An automatic algorithm was developed to classify the fruits based on the external color of them. Physical, mechanical and nutritional properties of fruits were determined to compare the results of image analysis and visual classification. During the process of image segmentation, the black spots on persimmon fruits were removed to dilute the effect of them on the features to be extracted and used for classification. Among the features, there were significant differences between maturity stages for mean values of R, G, b*, gray scale and S channels. Two classifiers based on linear (LDA) and quadratic discriminant analysis (QDA) were used to assess the applicability of vision system. The results showed that QDA classifier could be valuable in categorizing the fruits with better overall accuracy rate of 90.24%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.