Radon-based image processing in a parallel pipeline architecture

This paper deals with a novel architecture that makes real-time projection-based algorithms a reality. The design is founded on raster-mode processing, which is exploited in a powerful and flexible pipeline. This architecture, dubbed "P3 E"(Parallel Pipeline Projection Engine), supports a large variety of image processing and image analysis applications. The image processing applications include: Discrete approximations of the Radon and inverse Radon transform, among other projection operators; CT reconstructions; 2-D convolutions; rotations and translations; discrete Fourier transform computations in polar coordinates; autocorrelations; etc. There is also an extensive list of key image analysis algorithms that are supported by P E, thus making it a profound and versatile tool for projection-based computer vision. These include: projections of gray-level images along linear patterns (the Radon transform) and other curved contours; generation of multi-color digital masks; convex hull approximations; Hough transform approximations for line and curve detection; diameter computations; calculations of moments and other principal components; etc. The effectiveness of our approach and the feasibility of the proposed architecture have been demonstrated by running some of these image analysis algorithms in conventional short pipelines, to solve some important automated inspection problems. In the present paper, we will concern ourselves with reconstructing images from their linear projections, and performing convolutions via the Radon transform. © 1986 SPIE.