| dc.description.abstract | A computer vision system was implemented to identify the ripening stages of bananas based on color, development of brown spots, and image texture information. Nine simple features of appearance (L* a*, b* values; brown area percentage, number of brown spots per cm(2); and homogeneity, contrast, correlation: and entropy of image texture) extracted from images of bananas were used for classification purposes. Results show that in spite of variations in data for color and appearance, a simple classification technique is as good to identify the ripening stages of bananas as professional visual perception. Using L* a*, b* bands, brown area percentage, and contrast,it was possible to classify 49 banana samples in their 7 ripening stages with an accuracy of 98%. Computer vision shows promise for online prediction of ripening stages of bananas. | |
