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Optical Engineering

Image binarization techniques for correlation-based pattern recognition
Author(s): W. C. Hasenplaugh; Mark Allen Neifeld
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Paper Abstract

Correlation using binary images is suited to efficient digital realization or convenient optical implementation. Binarization algorithms are required in order to match grayscale imagery to these binary correlation architectures. We present several novel point-wise and block-wise binarization techniques all of which outperform the grayscale matched filter for large values of input signal-to-noise ratio (SNR=0dB). We discuss direct binarization methods based on global thresholds, local thresholds, histogram equalization, edge-enhancement, and statistical binarization, as well as indirect methods based on auto- and crosscorrelation techniques. These point-wise methods are shown to offer poor noise tolerance and a new block-wise binarization method is introduced to enhance recognition at low values of SNR. This block-wise technique is motivated by vector quantization-based image compression and offers performance superior to the grayscale matched filter for an input SNR as low as -12 dB.

Paper Details

Date Published: 1 November 1999
PDF: 11 pages
Opt. Eng. 38(11) doi: 10.1117/1.602241
Published in: Optical Engineering Volume 38, Issue 11
Show Author Affiliations
W. C. Hasenplaugh, Univ. of Arizona (United States)
Mark Allen Neifeld, Optical Sciences Ctr./Univ. of Arizona (United States)

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