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Optical Engineering

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network
Author(s): Nong Sang; Tianxu Zhang
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Paper Abstract

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network’s massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point pattern relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

Paper Details

Date Published: 1 December 1997
PDF: 8 pages
Opt. Eng. 36(12) doi: 10.1117/1.601577
Published in: Optical Engineering Volume 36, Issue 12
Show Author Affiliations
Nong Sang, Huazhong Univ. of Science and Technology (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)


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