Object-Based Segmentation And Color Recognition In Multispectral Images

It is difficult to segment an image according to object, for the geometry of lighting and viewing of three-dimensional objects incurs spatial inhomogeneities (highlights, shading, and cast shadows) in the image. However, the bands of a multispectral image can be used to do the segmentation. We start by assuming that the image field for a uniformly colored object is the sum of a small number of terms, each term being the product of a spatial and a spectral part. The physics of the spatial part is intricate, but the spatial part can be factored out to produce several space-invariant fields of numbers within reflectance boundaries. For an image field either from two light sources on a matte surface or from a single light source on a dielectric surface with highlights, the space-invariant quantities characterizing the object are the components of a particular unit vector in color space. The possibility is discussed of an algorithm for estimating the relative spectral reflectance of an object based on its space-invariant image fields.