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Proceedings Paper

Nondestructive and rapid detection of potato black heart based on machine vision technology
Author(s): Fang Tian; Yankun Peng; Wensong Wei
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Paper Abstract

Potatoes are one of the major food crops in the world. Potato black heart is a kind of defect that the surface is intact while the tissues in skin become black. This kind of potato has lost the edibleness, but it’s difficult to be detected with conventional methods. A nondestructive detection system based on the machine vision technology was proposed in this study to distinguish the normal and black heart of potatoes according to the different transmittance of them. The detection system was equipped with a monochrome CCD camera, LED light sources for transmitted illumination and a computer. Firstly, the transmission images of normal and black heart potatoes were taken by the detection system. Then the images were processed by algorithm written with VC++. As the transmitted light intensity was influenced by the radial dimension of the potato samples, the relationship between the grayscale value and the potato radial dimension was acquired by analyzing the grayscale value changing rule of the transmission image. Then proper judging condition was confirmed to distinguish the normal and black heart of potatoes after image preprocessing. The results showed that the nondestructive system built coupled with the processing methods was accessible for the detection of potato black heart at a considerable accuracy rate. The transmission detection technique based on machine vision is nondestructive and feasible to realize the detection of potato black heart.

Paper Details

Date Published: 17 May 2016
PDF: 7 pages
Proc. SPIE 9864, Sensing for Agriculture and Food Quality and Safety VIII, 98640T (17 May 2016); doi: 10.1117/12.2223292
Show Author Affiliations
Fang Tian, China Agricultural Univ. (China)
Yankun Peng, China Agricultural Univ. (China)
Wensong Wei, China Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 9864:
Sensing for Agriculture and Food Quality and Safety VIII
Moon S. Kim; Kuanglin Chao; Bryan A. Chin, Editor(s)

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