Object segmentation in poultry housings using spectral reflectivity

Abstract

We present a simple and robust method for pixel segmentation based on spectral reflectance properties.Of four object categories that are relevant for PoultryBot, a mobile robot for poultry housings, the spectral reflectance was measured at wavelengths between 400 and 1000 nm.From this information, the distribution of reflectance values was determined for each combination of object category and wavelength band measured.From this, the wavelength band could be selected where the overlap between objects was lowest.This was found to be around 467 nm, with 16% overlap for chickens vs. eggs, 12% overlap for housing vs. litter, and lower overlap for other combinations.Images were taken with a standard monochrome camera and a band pass filter around 470 nm in a commercial poultry house, to test segmentation using this method.Preliminary results indicate that this method is a promising direction for future work.