Classification of hyperspectral imagery for identifying fecal and ingesta contaminants

Bosoon Park; William R. Windham; Kurt C. Lawrence; Douglas P. Smith

doi:10.1117/12.514724

30 March 2004 Classification of hyperspectral imagery for identifying fecal and ingesta contaminants

Bosoon Park, William R. Windham, Kurt C. Lawrence, Douglas P. Smith

Proceedings Volume 5271, Monitoring Food Safety, Agriculture, and Plant Health; (2004) https://doi.org/10.1117/12.514724
Event: Optical Technologies for Industrial, Environmental, and Biological Sensing, 2003, Providence, RI, United States

Abstract

This paper presents the research results of the performance of classification methods for hyperspectral poultry imagery to identify fecal and ingesta contaminants on the surface of broiler carcasses. A pushbroom line-scan hyperspectral imager was used to acquire hyperspectral data with 512 narrow bands covered from 400 to 900 nm wavelengths. Three different feces from digestive tracts (duodenum, ceca, colon), and ingesta were used as contaminants. These contaminants were collected from the broiler carcasses fed by corn, milo, and wheat with soybean meals. For the selection of optimum classifier, various widely used supervised classification methods (parallelepiped, minimum distance, Mahalanobis distance, maximum likelihood, spectral angle mapper, and binary coding) were investigated. The classification accuracies ranged from 62.94% to 92.27%. The highest classification accuracy for identifying contaminants for corn fed carcasses was 92.27% with spectral angle mapper classifier. While, the classification accuracy was 82.02% with maximum likelihood method for milo fed carcasses and 91.16% accuracy was obtained for wheat fed carcasses when same classification method was used. The mean classification accuracy obtained in this study for classifying fecal and ingesta contaminants was 90.21%.

Citation Download Citation

Bosoon Park, William R. Windham, Kurt C. Lawrence, and Douglas P. Smith "Classification of hyperspectral imagery for identifying fecal and ingesta contaminants", Proc. SPIE 5271, Monitoring Food Safety, Agriculture, and Plant Health, (30 March 2004); https://doi.org/10.1117/12.514724

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