In this paper we present an overview of the impact of optical technology on parallel image computing. We study a few efficient and simple optical organizations for a set of preprocessing tasks such as texture analysis, histograming, edge detection, dilation and contraction. Based on a generic parallel model of computation with optical interconnects called OMC, we then discuss a set of parallel architectures and algorithms for fine grain intermediate vision processing. These include optimal solutions to problems such as connectivity and proximity using massively parallel optical arrays. In conclusion, we concentrate on higher level image understanding issues such as feature extraction and pattern recognition.

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Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

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Department, Program, or Center

Computer Engineering (KGCOE)


RIT – Main Campus