Extracting arbitrary geometric primitives represented by Fourier descriptors

In this paper we present a novel formulation for the extraction of arbitrary shapes in model-based recognition. The formulation is based on the mapping defined in the Hough transform. We develop this mapping for the analytic representation of a shape characterised by a Fourier parameterisation. Edge direction information is included in the formulation as a way of reducing the computational requirements in the extraction process. The proposed approach extends the analytic formulation of the Hough transform to arbitrary shapes. An analytic representation provides a compact and extensive coverage of a shape which leads to an accurate and efficient evidence accumulation process. Experimental results show that the new approach can handle noise and occlusion in synthetic and real images