Parallel Implementation Of The Split And Merge Algorithm On Hypercube Processors For Object Detection And Recognition

Mehmet Celenk; Prabhashankar Lakshman

doi:10.1117/12.969276

21 March 1989 Parallel Implementation Of The Split And Merge Algorithm On Hypercube Processors For Object Detection And Recognition

Mehmet Celenk, Prabhashankar Lakshman

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Proceedings Volume 1095, Applications of Artificial Intelligence VII; (1989) https://doi.org/10.1117/12.969276
Event: SPIE 1989 Technical Symposium on Aerospace Sensing, 1989, Orlando, FL, United States

Abstract

Split and merge is a computationaly efficient region segmentation technique suitable to detect objects or surfaces in a given image. Despite its superior performance, it suffers from large memory usage and excessive computation time. This paper describes parallel implementation of the split and merge algorithm in a 16 node hypercube processor in order to reduce processing time to an acceptable level in the real time applications. Three methods are proposed to parallelize the operation of the method using the nearest neghbor (mesh) topology that can be mapped onto the hypercube architecture. Comparison of the described techniques is given and processing results of the real world images are presented.

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Mehmet Celenk and Prabhashankar Lakshman "Parallel Implementation Of The Split And Merge Algorithm On Hypercube Processors For Object Detection And Recognition", Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); https://doi.org/10.1117/12.969276

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