Recognizing Color Patterns Irrespective of Viewpoint and Illumination

New invariant features are presented that can be used for the recognition of planar color patterns such as labels , logos, signs, pictograms, etc., irrespective of the viewpoint or the illumination conditions, and without the need for error prone contour extraction. The new features are based on moments of powers of the intensities in the individual color bands and combinations thereof. These moments implicitly characterize the shape, the intensity and the color distribution of the pattern in a uniform manner. The paper gives a classiication of all functions of such moments which are invariant under both aane deformations of the pattern (thus achieving viewpoint invari-ance) as well as linear changes of the intensity values of the color bands (hence, coping with changes in the irradiance pattern due to diierent lighting conditions and/or viewpoints). The discriminant power and clas-siication performance of the new invariants for color pattern recognition is tested on a data set of images of real, outdoors advertising panels. A comparison to moment invariants presented in literature is included as well.