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Proceedings Paper

Intensity compensation for on-line detection of defects on fruit
Author(s): James Zhiqing Wen; Yang Tao
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Paper Abstract

A machine-vision sorting system was developed that utilizes the difference in light reflectance of fruit surfaces to distinguish the defective and good apples. To accommodate to the spherical reflectance characteristics of fruit with curved surface like apple, a spherical transform algorithm was developed that converts the original image to a non-radiant image without losing defective segments on the fruit. To prevent high-quality dark-colored fruit form being classified into the defective class and increase the defect detection rate for light-colored fruit, an intensity compensation method using maximum propagation was used. Experimental results demonstrated the effectiveness of the method based on maximum propagation and spherical transform for on-line detection of defects on apples.

Paper Details

Date Published: 30 October 1997
PDF: 8 pages
Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); doi: 10.1117/12.292772
Show Author Affiliations
James Zhiqing Wen, Univ. of Arkansas (United States)
Yang Tao, Univ. of Arkansas (United States)


Published in SPIE Proceedings Vol. 3164:
Applications of Digital Image Processing XX
Andrew G. Tescher, Editor(s)

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