Abstract

This paper shows how local directional entropy can be used as a tool to build up a robust local image descriptor for image feature extraction. Among other possible choices, the Renyi entropy has been selected as the main technique for this application. Local directional entropy which is related with the anisotropy images has been considered here as the basis for the design of a new Renyi entropy-based local image descriptor (RELID). The properties of this new descriptor are described and evaluated. The experimental results confirm that the new descriptor is endowed by most of the invariant properties desired for object recognition applications.

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