Orthogonal multiprocessor sharing memory with an enhanced mesh for integrated image understanding

Abstract This paper proposes a new parallel architecture, which has the potential to support low-level image processing as well as intermediate and high-level vision analysis tasks efficiently. The integrated architecture consists of an SIMD mesh of processors enhanced with multiple broadcast buses, and MIMD multiprocessor with orthogonal access buses, and a two-dimensional shared memory array. Low-level image processing is performed on the mesh processor, while intermediate and high-level vision analysis is performed on the orthogonal multiprocessor. The interaction between the two levels is supported by a common shared memory. Concurrent computations and I/O are made possible by partitioning the memory into disjoint spaces so that each processor system can access a different memory space. To illustrate the power of such a two-level system, we present efficient parallel algorithms for a variety of problems from low-level image processing to high-level vision. Representative problems include matrix based computations, histogramming and key counting operations, image component labeling, pyramid computations, Hough transform, pattern clustering, and scene labeling. Through computational complexity analysis, we show that the integrated architecture meets the processing requirements of most image understanding tasks.