An optical processor that realizes a generalized chord transformation is described. The wedge-ring detector samples of an autocorrelation are shown to be the histograms of the chord distributions. This dimensionality reduced set of features is used as the feature vector inputs for a Fisher linear classifier to determine the class of the input object independent of geometrical distortions. Initial discussions on the use of different classifiers, the polarity of the classifier’s output, and selection of the image training set are also advanced.
© 1983 Optical Society of America
David Casasent and Wen-Thong Chang, "Generalized chord transformation for distortion-invariant optical pattern recognition," Appl. Opt. 22, 2087-2094 (1983)