Improved Forward Floating Selection Algorithm for Chicken Contaminant Detection in Hyperspectral Imagery

摘要

Reduction of the potential health risks to consumers caused by food-borne infections is a very important food safety issue of public concern; one of the leading causes of food-borne illnesses is fecal contamination. We consider detecting fecal contaminants on chicken carcasses using hyperspectral imagery. We introduce our new improved forward floating selection (IFFS) algorithm for feature selection of the wavebands to use in hyperspectral data for classification. Our IFFS algorithm is an improvement on the state-of-the-art sequential forward floating selection (SFFS) algorithm. Our initial results indicate that our method gives an excellent detection rate and performs better than other quasi-optimal feature selection algorithms.