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IMAGE PROCESSING, PATTERN RECOGNITION
Near-duplicate image recognition based on the rank distribution of the brightness clusters cardinality
V. B. Nemirovskiy, A. K. Stoyanov Institute of Cybernetics, National Research Tomsk Polytechnic University
Abstract:
In this paper the usage of multi-step segmentation for near-duplicate image recognition is investigated. The clustering of image pixels brightness is used for segmentation. The clustering is realized by means of a recurrent neural network.
The search pattern based on the rank distributions of the brightness clusters cardinality is suggested. Experimental results on the near-duplicate image recognition based on the application of the suggested search pattern are given. It is shown that the use of a multi-step segmentation and rank distributions of the brightness clusters cardinality allows one to successfully recognize the duplicates, which are received by a considerable visual distortion of the original image or by the change of image scale.
Keywords:
image, pixel, point mapping, recurrent neural network, clustering, segmentation, image recognition, ranking distribution.
Received: 15.06.2014
Citation:
V. B. Nemirovskiy, A. K. Stoyanov, “Near-duplicate image recognition based on the rank distribution of the brightness clusters cardinality”, Computer Optics, 38:4 (2014), 811–817
Linking options:
https://www.mathnet.ru/eng/co195 https://www.mathnet.ru/eng/co/v38/i4/p811
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Abstract page: | 152 | Full-text PDF : | 77 | References: | 28 |
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