Paper
12 October 2007 Contaminant detection on poultry carcasses using hyperspectral data: Part II. Algorithms for selection of sets of ratio features
Songyot Nakariyakul, David P. Casasent
Author Affiliations +
Abstract
We consider new methods to select useful sets of ratio features in hyperspectral data to detect contaminant regions on chicken carcasses using data provided by ARS (Athens, GA). A ratio feature is the ratio of the response at each pixel for two different wavebands. Ratio features perform a type of normalization and can thus help reduce false alarms, if a good normalization algorithm is not available. Thus, they are of interest. We present a new algorithm for the general problem of such feature selection in high-dimensional data. The four contaminant types of interest are three types of feces from different gastrointestinal regions (duodenum, ceca, and colon) and ingesta (undigested food) from the gizzard. To select the best two sets of ratio features from this 492-band HS data requires an exhaustive search of more than seven billion combinations of two sets of ratio features, which is very excessive. Thus, we propose our new fast ratio feature selection algorithm that requires evaluation of a much fewer number of sets of ratio features and is capable of giving quasi-optimal or optimal sets of ratio features. This new feature selection method has not been previously presented. It is shown to offer promise for an excellent detection rate and a low false alarm rate for this application. Our tests use data with different feed types and different contaminant types.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Songyot Nakariyakul and David P. Casasent "Contaminant detection on poultry carcasses using hyperspectral data: Part II. Algorithms for selection of sets of ratio features", Proc. SPIE 6761, Optics for Natural Resources, Agriculture, and Foods II, 67610S (12 October 2007); https://doi.org/10.1117/12.734593
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Databases

Feature selection

Feature extraction

Forward error correction

Inspection

Skin

Colon

Back to Top