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Proceedings Article

Compact multispectral imaging system for contaminant detection on poultry carcass

[+] Author Affiliations
Michio Kise, Bosoon Park, Kurt C. Lawrence, William R. Windham

USDA Agricultural Research Service

Proc. SPIE 6503, Machine Vision Applications in Industrial Inspection XV, 650305 (February 17, 2007); doi:10.1117/12.711035
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From Conference Volume 6503

  • Machine Vision Applications in Industrial Inspection XV
  • Fabrice Meriaudeau; Kurt S. Niel
  • San Jose, CA, USA | January 28, 2007

abstract

The objective of this research was to design and fabricate a compact, cost effective multispectral instrument and to collect and analyze spectra for real-time contaminant detection for poultry processing plants. The prototype system developed in this research consisted of a multispectral imaging system, illumination system and an industrial portable computer. The dual-band spectral imaging system developed in this study was a two-port imaging system that consisted of two identical monochrome cameras, optical system and two narrow bandpass filters whose center of the wavelength are 520 and 560 nm with 10 nm FWHM, respectively. A spectral reflectance from a chicken carcass was collected and split in two directions by an optical system including a beamsplitter and lenses, and then two identical collimated lights were filtered by the narrow bandpass filters and delivered to the cameras. Lens distortions and geometric misalignment of the two cameras were mathematically corrected. The prototype system was tested at the real-time processing line and the preliminary results showed that the dual-band spectral imaging system could effectively detect feces and ingesta on the surface of poultry carcass.

© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Michio Kise ; Bosoon Park ; Kurt C. Lawrence and William R. Windham
"Compact multispectral imaging system for contaminant detection on poultry carcass", Proc. SPIE 6503, Machine Vision Applications in Industrial Inspection XV, 650305 (February 17, 2007); doi:10.1117/12.711035; http://dx.doi.org/10.1117/12.711035


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