Near-duplicate image recognition based on the rank distribution of the brightness clusters cardinality

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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.

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Image, pixel, point mapping, recurrent neural network, clustering, segmentation, image recognition, ranking distribution

Короткий адрес: https://sciup.org/14059312

IDR: 14059312

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