Vision based fruit sorting system using measures of fuzziness and degree of matching

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Title:	Vision based fruit sorting system using measures of fuzziness and degree of matching
Authors:	Lin, Sinn-cheng;Chen, Yung-yaw
Contributors:	淡江大學資訊與圖書館學系
Date:	1994-10
Issue Date:	2011-05-20 09:51:18 (UTC+8)
Abstract:	Fuzzy approaches were used to determine optimal thresholding values of fruit's images, and fuzzy degree of matching was applied to classify the color and size of fruit. Results showed that fuzzy method was superior to the traditional statistical methods, and a accuracy of 93.3% for combined sorting was reported. The errors due to miscategorization could thus be reduced if the fuzzy methods were used. The developed fuzzy algorithms were integrated with the machine vision guided robotic sorting system for fruits.
Relation:	IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX , USA
Appears in Collections:	[Graduate Institute & Department of Information and Library Sciences] Proceeding

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