Shape Description and Invariant Recognition Employing Connectionist Approach

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Shape Description and Invariant Recognition Employing Connectionist Approach
This paper presents a new approach for shape description and invariant recognition by geometric-normalization implemented by neural networks. The neural system consists of a shape description network, a normalization network and a recognition stage based on fuzzy pyramidal neural networks. The description network uses a novel approach for hierarchical shape segmentation and representation which expands the image shapes into localized feature tokens. These feature tokens form a compact description of the shape and its components that include information on their location, size and orientation. The description network, which is composed of a novel pyramidal architecture called the Vectorial Gradual Lattice Pyramid, processes in parallel a new vectorial scale space representation of the shape. A novel measure called Cancellation Energy is used to determine the feature tokens. The normalization network utilizes the location, size, and orientation information in the feature tokens to geome...
Jezekiel Ben-Arie, Zhiqian Wang
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Authors Jezekiel Ben-Arie, Zhiqian Wang
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