Abstract

An image-classification algorithm based on an alphabet of local binary patterns is described. The efficiency of the proposed algorithm is demonstrated using a test image set of handwritten digits (MNIST). A comparison of the algorithm’s properties with similar results to those of convolutional artificial neural networks is presented.

© 2021 Optical Society of America

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