Spiral Object Recognition on Clusters

Object matching has many potential applications in industry, defense and medical science. Most matching methods introduced in recent years are based on the invariant representations. Main invariants applied in computer vision are algebraic, differential invariants and integral invariants. Our approach in this paper uses an affine integral invariant within a Spiral Architecture. The invariant representation is based on the extracted object contour. The parameter to be used for parameterizing an object contour is derived from the enclosed area. The Spiral Architecture posseses powerful computation features that are pertinent to the vision process. We present a parallel algorithm for object recognition on clusters. Image partitioning based on Spiral Architecture provides well-balanced load and absolutely uniform sub-images. The cluster-based object recognition greatly inC1'eases computation speed.