Sorting Raisins by Machine Vision System

Mahdi Abbasgholipour, Mahmoud Omid, Alireza Keyhani and Seydsaeid Mohtasebi

Modern Applied Science, 2010, vol. 4, issue 2, 49

Abstract: In this research, an apparatus for sorting raisins has been designed and fabricated based on machine vision system. This system was composed of conveyor belt, lighting box, controlling and processing system unit and sorting unit. Color feature is the most important parameter in classification and sorting of raisins. In order to carry out image processing and to extract useful features of captured images by machine vision a highly efficient algorithm was developed and implemented in Visual Basic 6.0 environment. The algorithm was consisted of background segmentation, raisin selection and feature extraction. The developed algorithm initially extracts the raisins by removing the background from the taken images. It then sorts the raisins according to their HSI color and size features. By a suitable combination of length and HSI color values raisins were graded it two classes. The final step in the algorithm was the calculation of the center of gravity of each raisin to be later used for automatic sorting and rejection of bad raisins. In order to evaluate the precision of the sorter statistical analysis was carried out. Experimental results indicated the accuracy of the proposed system is about 93 percent. The system can be easily adapted for sorting other agricultural products such as lentil and almond.

Date: 2010
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