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Automatic Color-Matching Model of Environmental Art Based on Visual Matching by Using IoT
In order to improve the matching effect of environmental art color automatic matching, a model of environmental art color automatic matching based on visual matching is designed. Firstly, it preprocesses the color matching of environmental art, then extracts the color space and its main color, and a...
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Published in: | Wireless communications and mobile computing 2022-09, Vol.2022, p.1-7 |
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container_title | Wireless communications and mobile computing |
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creator | Hu, Deqiang Hou, Xugang Song, Nan |
description | In order to improve the matching effect of environmental art color automatic matching, a model of environmental art color automatic matching based on visual matching is designed. Firstly, it preprocesses the color matching of environmental art, then extracts the color space and its main color, and analyzes the color deviation. At the same time, the color model is established and the color quantization is processed, and finally the color matching is realized. The experimental results show that the matching time of the proposed model is less than that of the traditional model, and the wrong contour is less. Research Objective. A model of environmental art color-automated matching based on visual matching is developed in order to improve the matching effect of environmental art color matching. Current Challenges. Because of time constraints, the matching model still has certain drawbacks, necessitating more optimization research in the subsequent study. The main steps in the research are pretreatment before color matching of environmental art, color space and main color extraction, color deviation analysis, color modeling, color quantization processing, implementation of color matching, and experimental comparison. |
doi_str_mv | 10.1155/2022/9100991 |
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Firstly, it preprocesses the color matching of environmental art, then extracts the color space and its main color, and analyzes the color deviation. At the same time, the color model is established and the color quantization is processed, and finally the color matching is realized. The experimental results show that the matching time of the proposed model is less than that of the traditional model, and the wrong contour is less. Research Objective. A model of environmental art color-automated matching based on visual matching is developed in order to improve the matching effect of environmental art color matching. Current Challenges. Because of time constraints, the matching model still has certain drawbacks, necessitating more optimization research in the subsequent study. The main steps in the research are pretreatment before color matching of environmental art, color space and main color extraction, color deviation analysis, color modeling, color quantization processing, implementation of color matching, and experimental comparison.</description><identifier>ISSN: 1530-8669</identifier><identifier>EISSN: 1530-8677</identifier><identifier>DOI: 10.1155/2022/9100991</identifier><language>eng</language><publisher>Oxford: Hindawi</publisher><subject>Color ; Color matching ; Constraint modelling ; Contour matching ; Designers ; Deviation ; Environmental art ; Internet of Things ; Measurement ; Model matching ; Neighborhoods ; Optimization ; Semantics</subject><ispartof>Wireless communications and mobile computing, 2022-09, Vol.2022, p.1-7</ispartof><rights>Copyright © 2022 Deqiang Hu et al.</rights><rights>Copyright © 2022 Deqiang Hu et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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The main steps in the research are pretreatment before color matching of environmental art, color space and main color extraction, color deviation analysis, color modeling, color quantization processing, implementation of color matching, and experimental comparison.</description><subject>Color</subject><subject>Color matching</subject><subject>Constraint modelling</subject><subject>Contour matching</subject><subject>Designers</subject><subject>Deviation</subject><subject>Environmental art</subject><subject>Internet of Things</subject><subject>Measurement</subject><subject>Model matching</subject><subject>Neighborhoods</subject><subject>Optimization</subject><subject>Semantics</subject><issn>1530-8669</issn><issn>1530-8677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNp9kMFKAzEQhoMoWKs3HyDgUddOks1mc6ylaqHFSyt4CtlNVrdsNzXJKn17t7T06Gl-hm9mmA-hWwKPhHA-okDpSBIAKckZGhDOIMkzIc5POZOX6CqENQAwoGSAPsZddBsd6xJPXON8stCx_KrbT7xwxjbYVXja_tTetRvbRt3gsY_4SQdrsGvxex26vneaKXZ4FfZh5pbX6KLSTbA3xzpEq-fpcvKazN9eZpPxPCkZEzHJGRUVlKnRVUoJEzlYk-U5YcChAGlSLnjKwHJTAGfCCoCSUWI5kYxKAWyI7g57t959dzZEtXadb_uTioreSJpxkffUw4EqvQvB20ptfb3RfqcIqL08tZenjvJ6_P6A928Z_Vv_T_8BE7VrWg</recordid><startdate>20220919</startdate><enddate>20220919</enddate><creator>Hu, Deqiang</creator><creator>Hou, Xugang</creator><creator>Song, Nan</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0003-3771-6216</orcidid></search><sort><creationdate>20220919</creationdate><title>Automatic Color-Matching Model of Environmental Art Based on Visual Matching by Using IoT</title><author>Hu, Deqiang ; 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subjects | Color Color matching Constraint modelling Contour matching Designers Deviation Environmental art Internet of Things Measurement Model matching Neighborhoods Optimization Semantics |
title | Automatic Color-Matching Model of Environmental Art Based on Visual Matching by Using IoT |
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