Multi-Spectral Scale And Rotation Invariant Associative Memory Method For Pattern Recognition

Steven F. Kimball; Richard A. Messner

doi:10.1117/12.949029

7 March 1989 Multi-Spectral Scale And Rotation Invariant Associative Memory Method For Pattern Recognition

Steven F. Kimball, Richard A. Messner

Proceedings Volume 1005, Optics, Illumination, and Image Sensing for Machine Vision III; (1989) https://doi.org/10.1117/12.949029
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States

Abstract

The method of using log-polar mapping with spectral band separation to form feature vectors for an associative memory is investigated. Log-polar mapping is used to provide the scale and rotation invariant properties. This reduces the teaching time and total capacity requirement for the associative memory because all orientations and sizes of the target object need not be learned. The images are also broken down into spatial frequency bands. The use of this technique is motivated by evidence that similar processes occur in the human visual system. Suspected benefits include enhanced recognition in the presence of noise and improved network robustness. Simulation results are presented for the case of character recognition.

Citation Download Citation

Steven F. Kimball and Richard A. Messner "Multi-Spectral Scale And Rotation Invariant Associative Memory Method For Pattern Recognition", Proc. SPIE 1005, Optics, Illumination, and Image Sensing for Machine Vision III, (7 March 1989); https://doi.org/10.1117/12.949029

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