Segmentation Of Specular Highlights From Object Surfaces

Abstract

A major hindrance to image segmentation tasks are the presence of specular highlights on object surfaces. Specular highlights appear on object surfaces where the specular component of reflection from illuminating light sources is so dominant that most detail of the object surface is obscured by a bright region of reflected light. Specular highlights are very common artifacts of most lighting environments and are not part of the intrinsic visible detail of an object surface. As a result, in addition to obscuring visible detail, specular highlight regions of an image can easily deceive image understanding algorithms into interpreting these regions as separate objects or regions on an object with high albedo. Recently, a couple of approaches to identifying specular highlight regions in images of object surfaces have produced some good results using color analysis. Unfortunately these methods work only for dielectric materials (e.g. plastic, rubber etc..) and require that the color of the object be different from the color of the light source. In this paper a technique is presented exploiting the polarization properties of reflected light to identify specular highlight regions. This technique works for both dielectric and metal surfaces regardless of the color of the illuminating light source, or the color detail on the object surface. In addition to separating out diffuse and specular components of reflection, the technique presented here also as a bonus can identify whether certain image regions correspond to a dielectric or metal object surface. Extensive experimentation will be presented for a variety of dielectric and metal surfaces, both polished and rough. Experimentation with coated surfaces using the technique presented here have not yet been studied.