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Proceedings Paper

Egg weight detection on machine vision system
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Paper Abstract

A machine vision system for egg weight detection was developed. Egg image was grabbed by a CCD camera and a frame grabber. An indicator composed of R, G, B intensity was used for image segmentation. A series of algorithms were developed to evaluate egg's vertical diameter, maximal horizontal diameter, upper horizontal diameter and nether horizontal diameter. Based on extracted four size features of vertical and maximal/upper/nether horizontal diameter, a regression model between egg's weight and its size was established using SAS, which was used to detect egg's weight. The experiment results indicated that, for egg weight detection on the machine vision system, the correlative coefficient of the regression model was 0.9781 and the absolute error was no more than ±3 g, which would be lower work load on human graders and an increased flexibility in the egg quality control process in egg's industrialization.

Paper Details

Date Published: 23 October 2006
PDF: 10 pages
Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 638114 (23 October 2006); doi: 10.1117/12.686479
Show Author Affiliations
Yike Cen, Zhejiang Univ. (China)
Yibin Ying, Zhejiang Univ. (China)
Xiuqin Rao, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 6381:
Optics for Natural Resources, Agriculture, and Foods
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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