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Proceedings Paper

Dynamically reconfigurable multiprocessor system for high-order-bidirectional-associative-memory-based image recognition
Author(s): Chwan-Hwa Wu; David A. Roland
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Paper Abstract

In this paper a high-order bidirectional associative memory (HOBAM) based image recognition system and a dynamically reconfigurable multiprocessor system that achieves real- time response are reported. The HOBAM has been utilized to recognize corrupted images of human faces (with hats, glasses, masks, and slight translation and scaling effects). In addition, the HOBAM, incorporated with edge detection techniques, has been used to recognize isolated objects within multiple-object images. Successful recognition rates have been achieved. A dynamically reconfigurable multiprocessor system and parallel software have been developed to achieve real-time response for image recognition. The system consists of Inmos transputers and crossbar switches (IMS C004). The communication links can be dynamically connected by circuit switching. This is the first time and the transputers and crossbar switches are reported to form a low-cost multiprocessor system connected by a switching network. Moreover, the switching network simplifies the design of the communication in parallel software without handling the message routing. Although the HOBAM is a fully connected network, the algorithm minimizes the amount of information that needs to be exchanged between processors using a data compression technique. The detailed design of both hardware and software are discussed in the paper. Significant speedup through parallel processing is accomplished. The architecture of the experimental system is a cost-effective design for an embedded system for neural network applications on computer vision.

Paper Details

Date Published: 1 August 1991
PDF: 12 pages
Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); doi: 10.1117/12.44880
Show Author Affiliations
Chwan-Hwa Wu, Auburn Univ. (United States)
David A. Roland, Auburn Univ. (United States)


Published in SPIE Proceedings Vol. 1471:
Automatic Object Recognition
Firooz A. Sadjadi, Editor(s)

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