A RECONFIGURABLE ARCHITECTURE FOR IMAGE PROCESSING AND COMPUTER VISION

Abstract

In this paper we describe a reconfigurable architecture for image processing and computer vision based on a multi-ring network which we call a Reconfigurable Multi-Ring System (RMRS). We describe the reconfiguration switch for the RMRS and also describe its VLSI implementation. The RMRS topology is shown to be regular and scalable and hence well-suited for VLSI implementation. We prove some important properties of the RMRS topology and show that a broad class of algorithms for the n-cube can be mapped to the RMRS in a simple and elegant manner. We design and analyze a class of procedural primitives for the SIMD RMRS and show how these primitives can be used as building blocks for more complex parallel operations. We demonstrate the usefulness of the RMRS for problems in image processing and computer vision by considering two important operations—the Fast Fourier Transform (FFT) and the Hough transform for detection of linear features in an image. Parallel algorithms for the FFT and the Hough transform on the SIMD RMRS are designed using the aforementioned procedural primitives. The analysis of the complexity of these algorithms shows that the SIMD RMRS is a viable architecture for problems in computer vision and image processing.