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Parallel implementation of vision algorithms on distributed systems

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2 Author(s)
You, J. ; Sch. of Comput. & Inf. Technol., Griffith Univ., Brisbane, Qld., Australia ; Hungenahally, S.

Vision computing involves the execution of a large number of operations on large sets of structured data. The need to implement vision tasks in parallel arises from the speed requirements of real-time environments in various application domains. In this paper we propose that a distributed computer system can be utilised to replace the specialised machine for the parallel implementation of vision tasks. We introduce some techniques used in distributed systems and adopt a divide-and-conquer policy to schedule the complex vision tasks for parallelism. Two traditional vision algorithms for matrix operation and image matching are implemented using PVM (parallel virtual machine). Furthermore, a hierarchical object recognition system is described as an example of parallelism on distributed systems. Finally we conclude that some vision tasks can be realised on a general distributed system to achieve the speedup at a low cost

Published in:

Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference on  (Volume:3 )

Date of Conference:

21-23 Apr 1998