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ARS Home » Research » Publications at this Location » Publication #174948
Title: IMPROVED IMAGING SYSTEM FOR FECAL DETECTION

Author
item HEITSCHMIDT, G - UGA
item Lawrence, Kurt
item Windham, William
item Park, Bosoon

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 10/22/2004
Publication Date: 11/26/2004
Citation: Heitschmidt, G.W., Lawrence, K.C., Windham, W.R., Park, B. 2004. Improved imaging system for fecal detection. Proceedings of Optics East Society of Photo-Optical Instrumentation Engineers. 5587:112-120.

Interpretive Summary:

Technical Abstract: The Agricultural Research Service (ARS) has developed both a hyperspectral and a multispectral imaging system to detect fecal contaminants on poultry carcasses. The hyperspectral imaging system operates from about 400 to 1000 nm, but only a few wavelengths are used in a real-time multispectral system. ARS has patented a method and system for detecting contaminants and has reported that the ratio of reflectance images at 565 nm and 517 nm was able to identify fecal contaminants. However, this ratio alone also misclassified numerous non-fecal carcass features (false positives). Recently, modifications to the system, including improved lighting, a new hyperspectral imaging camera, and a new algorithm with an additional wavelength, have increased fecal detection accuracy while reducing the number of false positives. Additional lighting, targeted at critical areas of the carcass, has resulted in fewer shadows and less glare. New components in the hyperspectral imaging camera have effectively removed misregistration inherent in earlier models and has simplified wavelength and reflectance calibration. The addition of a third wavelength, coupled with a decision tree processing approach, has significantly reduced false positives associated with the 565/517-nm ratio. The new system was used to collect hyperspectral data on 56 stationary poultry carcasses. Carcasses were contaminated with both large and small spots of feces from the duodenum, ceca, and colon, and ingesta from the crop. There were a total of 1030 contaminants applied to the carcasses. The algorithm correctly identified over 99% of the contaminants with only 25 false positives. About a quarter of the carcasses had at least one false positive. The algorithms and new reflectance-value wavelengths will now be tested in a real-time multispectral imaging system for in-plant trials. Keywords. Poultry, Fecal, Ingesta, Pathogen, Hyperspectral