Abstract
A parallel algorithm for shape recognition is presented along with its implementation on a distributed memory multiprocessor. Shape recognition is one of the fundamental problems of computer vision. We consider a shape to be composed of a set of small straight line segments tangential to the object. The recognition problem is to determine whether the test image contains a specified reference shape or not. The straight line Hough transform (SLHT) has been used to detect reference shapes. A signature based parallel algorithm called SHARP is developed for shape recognition using SLHT on a distributed memory multiprocessor system. In the SHARP algorithm, the (θ, r) space is divided among processors. The SHARP algorithm has been implemented on a Meiko transputer with 32 nodes. We analyse the performance of the parallel algorithm using both theoretical and experimental techniques.
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