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A local color descriptor for efficient scene-object recognition

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3 Author(s)
Bigorgne, E. ; Lab. des Instrum. et Syst. d''Ile de France, Univ. Pierre et Marie Curie, Paris, France ; Achard, C. ; Devars, Jean

This paper presents an effective use of local descriptors for object or scene recognition and indexing. This approach is in keeping with model-based recognition systems and consists of an extension of a standard point-to-point matching between two images. Aiming at this, we address the use of Full-Zernike moments as a reliable local characterization of the image signal. A fundamental characteristic of the used descriptors is then their ability to “absorb” a given set of potential image modifications. Their design calls principally for the theory of invariants. A built-in invariance to similarities allows one to manage narrow bounded perspective transformations. Moreover we provide a study of the substantial and costless contribution of the use of color information. In order to achieve photometric invariance, different types of normalization are evaluated through a model-based object recognition task

Published in:

Image Analysis and Processing, 2001. Proceedings. 11th International Conference on

Date of Conference:

26-28 Sep 2001