Contaminant detection on poultry carcasses using hyperspectral data: Part I. Algorithms for selection of individual wavebands

Songyot Nakariyakul; David P. Casasent

doi:10.1117/12.734582

12 October 2007 Contaminant detection on poultry carcasses using hyperspectral data: Part I. Algorithms for selection of individual wavebands

Songyot Nakariyakul, David P. Casasent

Author Affiliations +

Proceedings Volume 6761, Optics for Natural Resources, Agriculture, and Foods II; 67610R (2007) https://doi.org/10.1117/12.734582
Event: Optics East, 2007, Boston, MA, United States

Abstract

Contaminant detection on chicken carcasses is an important product inspection application. The four contaminant types of interest contain three types of feces from different gastrointestinal regions (duodenum, ceca, and colon) and ingesta (undigested food) from the gizzard. Use of automated or semi-automated inspection systems for detecting fecal contaminant regions is of great interest. Hyperspectral data provided by ARS (Athens, GA) were used to examine detection of contaminants on carcasses. We address quasi-optimal algorithms for selecting a set of spectral bands (wavelengths) in hyperspectral data for on-line contaminant detection (feature selection). We introduce our new improved forward floating selection (IFFS) algorithm and compare its performance to that of other state-of-the-art feature selection algorithms. Our initial results indicate that our method gives an excellent detection rate and performs better than other feature selection algorithms. We also show that combination feature selection algorithms perform worse.

Citation Download Citation

Songyot Nakariyakul and David P. Casasent "Contaminant detection on poultry carcasses using hyperspectral data: Part I. Algorithms for selection of individual wavebands", Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 67610R (12 October 2007); https://doi.org/10.1117/12.734582

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