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Proceedings Paper

Development of online line-scan imaging system for chicken inspection and differentiation
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Paper Abstract

An online line-scan imaging system was developed for differentiation of wholesome and systemically diseased chickens. The hyperspectral imaging system used in this research can be directly converted to multispectral operation and would provide the ideal implementation of essential features for data-efficient high-speed multispectral classification algorithms. The imaging system consisted of an electron-multiplying charge-coupled-device (EMCCD) camera and an imaging spectrograph for line-scan images. The system scanned the surfaces of chicken carcasses on an eviscerating line at a poultry processing plant in December 2005. A method was created to recognize birds entering and exiting the field of view, and to locate a Region of Interest on the chicken images from which useful spectra were extracted for analysis. From analysis of the difference spectra between wholesome and systemically diseased chickens, four wavelengths of 468 nm, 501 nm, 582 nm and 629 nm were selected as key wavelengths for differentiation. The method of locating the Region of Interest will also have practical application in multispectral operation of the line-scan imaging system for online chicken inspection. This line-scan imaging system makes possible the implementation of multispectral inspection using the key wavelengths determined in this study with minimal software adaptations and without the need for cross-system calibration.

Paper Details

Date Published: 23 October 2006
PDF: 10 pages
Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 63810Y (23 October 2006); doi: 10.1117/12.686087
Show Author Affiliations
Chun-Chieh Yang, USDA Agricultural Research Service (United States)
Diane E. Chan, USDA Agricultural Research Service (United States)
Kuanglin Chao, USDA Agricultural Research Service (United States)
Yud-Ren Chen, USDA Agricultural Research Service (United States)
Moon S. Kim, USDA Agricultural Research Service (United States)

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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