Abstract
An Innovative approach for representation and description of shape components for object recognition based on complex potential is proposed. In the complex plane, the flow of velocity is a crucial factor to discriminate different shapes. Hence, the present paper computes the potential flow by transforming the shape of the input object into complex plane. The present paper computes the Vortex based Complex Potential signature (VCP) by considering the radial lines as Equipotential lines and the circles as streamlines. The proposed VCP signature is described with the Fourier transformation for the generation of feature vector. The Chebyshev distance measure is used in the shape toning stage. The efficiency of the proposed descriptor is evaluated with the MPEG-CE-1 Set B database. The results prove the competency of the proposed descriptor than the benchmark descriptors
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