Color-Shape Context for Object Recognition

We propose a new image feature that merges color and shape information. This global feature, which we call color shape context, is a histogram that combines the spatial (shape) and color information of the image in one compact representation. This histogram codes the locality of color transitions in an image. Illumination invariant derivatives are first computed and provide the edges of the image, which is the shape information of our feature. These edges are used to obtain similarity (rigid) invariant shape descriptors. The color transitions that take place on the edges are coded in an illumination invariant way and are used as the color information. The color and shape information are combined in one multidimensional vector. The matching function of this feature is a metric and allows for existing indexing methods such as R-trees to be used for fast and efficient retrieval.