A class of processors which perform local neighborhood or cellular operations has well-documented applications in image processing.The architectural feature which unites these processors is their use of special -purpose hardware to compute image transformations based both on the values and on the spatial relationship of pixels in the input image. Typical operations include 3 x 3 convolution and mathematical morphology. Processing elements which compute cellular operations have been incorporated in a variety of system architectures. These range from single -processor, recirculating buffer systems to systems which have thousands of processors in a four -way interconnected mesh. Another feature which unites these processors is that they operate on images in the iconic domain. A new class of non -iconic processor is introduced here which uses image encoding schemes to reduce the number of operations required for certain classes of operations by between one and two orders of magnitude.
A review of computer architectures for machine vision applications is presented. Pipeline and cellular architectures for raster -to-raster and raster -to -list operations are described.Advantages and disadvantages of the various architectures are discussed.
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