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, 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 classification of all functions of such moments which are invariant under both affine deformations of the pattern (thus achieving viewpoint invariance) as well as linear changes of the intensity values of the color bands (hence, coping with changes in the irradiance pattern due to different lighting conditions and/or viewpoints). The discriminant power and classification performance of the new invariants for color pattern recognition is tested on a data set of images of outdoors advertising panels. A comparison to moment invariants presented in literature is included as well.

[1]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[2]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[3]  S. Maitra.  Moment invariants , 1979, Proceedings of the IEEE.

[4]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[5]  Oliver R. Hinton,et al.  About Moment Normalization and Complex Moment Descriptors , 1988, Pattern Recognition.

[6]  Andrew Zisserman,et al.  Geometric invariance in computer vision , 1992 .

[7]  Richard J. Prokop,et al.  A survey of moment-based techniques for unoccluded object representation and recognition , 1992, CVGIP Graph. Model. Image Process..

[8]  Andrew Zisserman,et al.  Applications of Invariance in Computer Vision , 1993, Lecture Notes in Computer Science.

[9]  Jan Flusser,et al.  Pattern recognition by affine moment invariants , 1993, Pattern Recognit..

[10]  Thomas H. Reiss,et al.  Recognizing Planar Objects Using Invariant Image Features , 1993, Lecture Notes in Computer Science.

[11]  Shree K. Nayar,et al.  Seeing Beyond Lambert's Law , 1994, ECCV.

[12]  Lawrence B. Wolff,et al.  On the relative brightness of specular and diffuse reflection , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[13]  Brian V. Funt,et al.  Color Constant Color Indexing , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Arnold W. M. Smeulders,et al.  A comparative study of several color models for color image invariant retrieval , 1996 .

[15]  Glenn Healey,et al.  The Illumination-Invariant Recognition of 3D Objects Using Local Color Invariants , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Luc Van Gool,et al.  Affine/ Photometric Invariants for Planar Intensity Patterns , 1996, ECCV.

[17]  Bernt Schiele,et al.  Comprehensive Colour Image Normalization , 1998, ECCV.