Automatic color pattern recognition of multispectral printed fabric images
Printed fabrics often have rich colors and variable patterns in different sizes and shapes, which make it difficult to achieve accurate pattern recognition and color measurement using traditional spectrophotometers and digital cameras. This paper develops a grid-based density peaks clustering (GDPC)...
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| Published in: | Journal of intelligent manufacturing Vol. 34; no. 6; pp. 2747 - 2763 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Springer US
01.08.2023
Springer Nature B.V |
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| ISSN: | 0956-5515, 1572-8145 |
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| Abstract | Printed fabrics often have rich colors and variable patterns in different sizes and shapes, which make it difficult to achieve accurate pattern recognition and color measurement using traditional spectrophotometers and digital cameras. This paper develops a grid-based density peaks clustering (GDPC) algorithm to automatically recognize patterns and extract colors of multispectral images of printed fabrics. The multispectral images captured by a self-developed multispectral imaging system is firstly converted into color images in CIELAB color space and three principal components are calculated by applying principal component analysis to reduce the dimensions of the multispectral images. During the multispectral image processing, the noise pixels are removed by calculating the local stability of each pixel, and then the remaining stable pixels are clustered using proposed GDPC algorithm based on three CIELAB color channels and three principal components. Compared with widely-used color clustering algorithms, the proposed GDPC algorithm can recognize the color patterns from more intricate multispectral printed fabric images with higher accuracy and less computational time. |
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| AbstractList | Printed fabrics often have rich colors and variable patterns in different sizes and shapes, which make it difficult to achieve accurate pattern recognition and color measurement using traditional spectrophotometers and digital cameras. This paper develops a grid-based density peaks clustering (GDPC) algorithm to automatically recognize patterns and extract colors of multispectral images of printed fabrics. The multispectral images captured by a self-developed multispectral imaging system is firstly converted into color images in CIELAB color space and three principal components are calculated by applying principal component analysis to reduce the dimensions of the multispectral images. During the multispectral image processing, the noise pixels are removed by calculating the local stability of each pixel, and then the remaining stable pixels are clustered using proposed GDPC algorithm based on three CIELAB color channels and three principal components. Compared with widely-used color clustering algorithms, the proposed GDPC algorithm can recognize the color patterns from more intricate multispectral printed fabric images with higher accuracy and less computational time. |
| Author | Wu, Hochung Xin, John H. Zhang, Jie Yao, Pengpeng |
| Author_xml | – sequence: 1 givenname: Jie orcidid: 0000-0001-8219-5590 surname: Zhang fullname: Zhang, Jie organization: School of Design, The Hong Kong Polytechnic University – sequence: 2 givenname: Pengpeng orcidid: 0000-0002-5961-1813 surname: Yao fullname: Yao, Pengpeng organization: Institute of Textiles and Clothing, The Hong Kong Polytechnic University – sequence: 3 givenname: Hochung surname: Wu fullname: Wu, Hochung organization: Institute of Textiles and Clothing, The Hong Kong Polytechnic University – sequence: 4 givenname: John H. orcidid: 0000-0001-9965-7421 surname: Xin fullname: Xin, John H. email: john.xin@polyu.edu.hk organization: Institute of Textiles and Clothing, The Hong Kong Polytechnic University |
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| DOI | 10.1007/s10845-022-01947-8 |
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| Keywords | Grid-based density peaks clustering algorithm Pattern recognition Printed fabrics Multispectral imaging method |
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| SubjectTerms | Advanced manufacturing technologies Algorithms Business and Management Clustering Color imagery Color measurement Computing time Control Digital cameras Fabrics Image processing Machines Manufacturing Mathematical analysis Mechatronics Pattern recognition Pixels Principal components analysis Processes Production Robotics Spectrophotometers |
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| Title | Automatic color pattern recognition of multispectral printed fabric images |
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