IMAGE PROCESSING, PATTERN RECOGNITION
Clustering face images
V. B. Nemirovskiy, A. K. Stoyanov
Institute of Cybernetics of Tomsk Polytechnic University, Tomsk, Russia
In this paper a multi-step algorithm for clustering face images is proposed. This algorithm is designed to split a collection of images into groups of similar images. The algorithm is based on clustering the proximity measures between brightness-based segmented images. As proximity measures, the Euclidean distance and the Kullback-Leibler distance were used. Brightness-based image segmentation and clustering respective proximity measures were carried out with the help of a software model of a recurrent neural network. Results of experimental studies of the proposed approach are presented.
image clustering, one-dimensional mapping, neuron, near-duplicate.
|The work is performed as part of the state task “Science”.
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V. B. Nemirovskiy, A. K. Stoyanov, “Clustering face images”, Computer Optics, 41:1 (2017), 59–66
Citation in format AMSBIB
\by V.~B.~Nemirovskiy, A.~K.~Stoyanov
\paper Clustering face images
\jour Computer Optics
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