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

Author

Chang, Wen-Hung ; Chen, Suming ; Lin, Sinn-Cheng ; Huang, Pai-Yi ; Chen, Yung-Yaw

Author_Institution

Dept. of Agric. Machinery Eng., Nat. Taiwan Univ., Taipei, Taiwan

Volume

3

fYear

1994

fDate

2-5 Oct 1994

Firstpage

2600

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

Keywords

computer vision; fuzzy systems; image classification; image matching; materials handling; robots; color classification; fruit images; fruit sorting system; fuzzy system; machine vision; optimal thresholding values; robots; size classification; Agricultural engineering; Agricultural machinery; Brightness; Image segmentation; Machine vision; Minimization methods; Pixel; Sorting; Statistical analysis; Turning;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-2129-4

Type

conf

DOI

10.1109/ICSMC.1994.400263

Filename

400263