Intelligent Retrieval Method of Approximate Painting in Digital Art Field

With the rapid development of Internet technology and the wide application of image acquisition equipment, the number of digital artwork images is exploding. The retrieval of near-similar artwork images has a wide application prospect for copyright infringement, trademark registration, and other sce...

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Autores principales:	Jixin Wan, Yu Xiaobo
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/ef90e35f8b6e46b68f03293801cebf75
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id	oai:doaj.org-article:ef90e35f8b6e46b68f03293801cebf75
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spelling	oai:doaj.org-article:ef90e35f8b6e46b68f03293801cebf752021-11-29T00:56:27ZIntelligent Retrieval Method of Approximate Painting in Digital Art Field1875-919X10.1155/2021/5796600https://doaj.org/article/ef90e35f8b6e46b68f03293801cebf752021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5796600https://doaj.org/toc/1875-919XWith the rapid development of Internet technology and the wide application of image acquisition equipment, the number of digital artwork images is exploding. The retrieval of near-similar artwork images has a wide application prospect for copyright infringement, trademark registration, and other scenes. However, compared with traditional images, these artwork images have the characteristics of high similarity and complexity, which lead to the retrieval accuracy not meeting the demand. To solve the above problems, an intelligent retrieval method of artwork image based on wavelet transform and dual propagation neural network (WTCPN) is proposed. Firstly, the original artwork image is replaced by the low-frequency subimage after wavelet transform, which not only removes redundant information and reduces the dimension of data but also suppresses random noise. Secondly, in order to make the network assign different competition winning units to different types of modes, the dual propagation neural network is improved by setting the maximum number of times of winning neurons. Experimental results show that the proposed method can improve the accuracy of image retrieval, and the recognition accuracy of verification set can reach over 91%.Jixin WanYu XiaoboHindawi LimitedarticleComputer softwareQA76.75-76.765ENScientific Programming, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer software QA76.75-76.765
spellingShingle	Computer software QA76.75-76.765 Jixin Wan Yu Xiaobo Intelligent Retrieval Method of Approximate Painting in Digital Art Field
description	With the rapid development of Internet technology and the wide application of image acquisition equipment, the number of digital artwork images is exploding. The retrieval of near-similar artwork images has a wide application prospect for copyright infringement, trademark registration, and other scenes. However, compared with traditional images, these artwork images have the characteristics of high similarity and complexity, which lead to the retrieval accuracy not meeting the demand. To solve the above problems, an intelligent retrieval method of artwork image based on wavelet transform and dual propagation neural network (WTCPN) is proposed. Firstly, the original artwork image is replaced by the low-frequency subimage after wavelet transform, which not only removes redundant information and reduces the dimension of data but also suppresses random noise. Secondly, in order to make the network assign different competition winning units to different types of modes, the dual propagation neural network is improved by setting the maximum number of times of winning neurons. Experimental results show that the proposed method can improve the accuracy of image retrieval, and the recognition accuracy of verification set can reach over 91%.
format	article
author	Jixin Wan Yu Xiaobo
author_facet	Jixin Wan Yu Xiaobo
author_sort	Jixin Wan
title	Intelligent Retrieval Method of Approximate Painting in Digital Art Field
title_short	Intelligent Retrieval Method of Approximate Painting in Digital Art Field
title_full	Intelligent Retrieval Method of Approximate Painting in Digital Art Field
title_fullStr	Intelligent Retrieval Method of Approximate Painting in Digital Art Field
title_full_unstemmed	Intelligent Retrieval Method of Approximate Painting in Digital Art Field
title_sort	intelligent retrieval method of approximate painting in digital art field
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/ef90e35f8b6e46b68f03293801cebf75
work_keys_str_mv	AT jixinwan intelligentretrievalmethodofapproximatepaintingindigitalartfield AT yuxiaobo intelligentretrievalmethodofapproximatepaintingindigitalartfield
_version_	1718407744146374656

Intelligent Retrieval Method of Approximate Painting in Digital Art Field

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