Application of Image Analysis for Classification of Ripening Bananas |
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Authors: | F Mendoza JM Aguilera |
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Affiliation: | Accepted 8/6/04. Authors Mendoza and Aquilera are with Dept. of Chemical Engineering and Bioprocesses, Pontificia Univ. Católicade Chile, P.O. Box 306, Santiago 22, Chile. Direct inquiries to author Mendoza (E-mail: ). |
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Abstract: | 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 cm2; 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. |
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Keywords: | computer vision ripening of bananas color appearance classification |
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