Dynamically reconfigurable multiprocessor system for high-order-bidirectional-associative-memory-based image recognition

Chwan-Hwa Wu; David A. Roland

doi:10.1117/12.44880

1 August 1991 Dynamically reconfigurable multiprocessor system for high-order-bidirectional-associative-memory-based image recognition

Chwan-Hwa Wu, David A. Roland

Author Affiliations +

Proceedings Volume 1471, Automatic Object Recognition; (1991) https://doi.org/10.1117/12.44880
Event: Orlando '91, 1991, Orlando, FL, United States

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.

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Chwan-Hwa Wu and David A. Roland "Dynamically reconfigurable multiprocessor system for high-order-bidirectional-associative-memory-based image recognition", Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); https://doi.org/10.1117/12.44880

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KEYWORDS

Switches

Switching

Object recognition

Computing systems

Image segmentation

Neural networks

Neurons

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