Colorimetric object classification

Abstract

In order to improve object recognition results, usually several image preprocessings are performed. If color images are used, a color normalization is normally applied. Algorithms for color normalization will be compared to a colorimetric approach found in the literature. Recovering colorimetric values instead of a simple RGB camera output leads to more reliable color images. To this kind of processed object image a basic object recognition approach using different histogram distances is applied. It will be shown that there is an effect on the results of object recognition rates if we use color calibrated images instead of color normalization methods.