A parallel algorithm and architecture for object recognition in images

The problem of tree pattern matching for object recognition in images is computationally intensive in nature. In two-dimensional images, the objects can be represented through multiscale decomposition as tree structures. The pattern tree representing an object can be matched with a subject tree representing an image in order to detect the objects within the image. Several sequential, parallel and hardware algorithms exist in the literature for tree pattern matching. In this paper, we describe a new parallel algorithm and its realization as a VLSI chip for tree pattern matching. The hardware algorithm is based on a linear array of processing elements (PEs) where the pattern matching is done in a pipelined fashion relying on nearest-neighbor communication between the PE´s and the subject and pattern trees of arbitrary length can be processed using a fixed size PE array. The algorithm has an improved execution time of O(lceilm/arceiln) required to perform the matching where m, a and n are the sizes of the pattern tree, processor array, subject tree respectively. A prototype CMOS VLSI chip implementing the proposed algorithm has been designed and verified. It is shown that the hardware algorithm proposed in this work represent a sign improvement in terms of computational complexity, data flow, and architecture over the ones previously proposed for this problem