Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China
This study aims to construct a new method for collecting colours from Guangzhou historical buildings using the Natural Color Sytem (NCS) colour system for on-site comparison. It seeks to detect and classify the primary and secondary colours of the buildings through image attributes, and to analyse t...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-10-01
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| Series: | Frontiers of Architectural Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095263525000081 |
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| author | Tianyi Fan Xiaoxiang Tang Kerun Li |
| author_facet | Tianyi Fan Xiaoxiang Tang Kerun Li |
| author_sort | Tianyi Fan |
| collection | DOAJ |
| description | This study aims to construct a new method for collecting colours from Guangzhou historical buildings using the Natural Color Sytem (NCS) colour system for on-site comparison. It seeks to detect and classify the primary and secondary colours of the buildings through image attributes, and to analyse the group co-occurrence and clustering algorithm characteristics of the colours of the historical buildings, as well as the colour hierarchy based on the image clustering algorithm. The study further evaluates the colour ratings of the historical buildings through questionnaire validation, explores the relationship between colour attributes (hue, lightness, and chroma), and classifies the colour evaluation criteria into five tiers. It was found that the symbiotic clustering diagrams of the colours of the historic buildings in Guangzhou exhibited distinct colour rating relationships, with the clustering colour hierarchy showing a high correlation with the results of the colour ratings assessed by questionnaire validation. A close relationship between the computer-generated output and the perceptual judgement is demonstrated, further proving the reliability and accuracy of the computer model. The results of the study provide comparable data and practical tools for colour planning and management of urban historic building facades. |
| format | Article |
| id | doaj-art-e8ff9b8ba44141daa0656c64dfb0eb1e |
| institution | Kabale University |
| issn | 2095-2635 |
| language | English |
| publishDate | 2025-10-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Frontiers of Architectural Research |
| spelling | doaj-art-e8ff9b8ba44141daa0656c64dfb0eb1e2025-08-20T03:58:07ZengKeAi Communications Co., Ltd.Frontiers of Architectural Research2095-26352025-10-011451415143510.1016/j.foar.2025.01.003Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, ChinaTianyi Fan0Xiaoxiang Tang1Kerun Li2Faculty of Innovation and Design, City University of Macau, Macau 999078, ChinaFaculty of Innovation and Design, City University of Macau, Macau 999078, China; School of Architecture, South China University of Technology, Guangzhou 510000, ChinaFaculty of Innovation and Design, City University of Macau, Macau 999078, China; Corresponding author.This study aims to construct a new method for collecting colours from Guangzhou historical buildings using the Natural Color Sytem (NCS) colour system for on-site comparison. It seeks to detect and classify the primary and secondary colours of the buildings through image attributes, and to analyse the group co-occurrence and clustering algorithm characteristics of the colours of the historical buildings, as well as the colour hierarchy based on the image clustering algorithm. The study further evaluates the colour ratings of the historical buildings through questionnaire validation, explores the relationship between colour attributes (hue, lightness, and chroma), and classifies the colour evaluation criteria into five tiers. It was found that the symbiotic clustering diagrams of the colours of the historic buildings in Guangzhou exhibited distinct colour rating relationships, with the clustering colour hierarchy showing a high correlation with the results of the colour ratings assessed by questionnaire validation. A close relationship between the computer-generated output and the perceptual judgement is demonstrated, further proving the reliability and accuracy of the computer model. The results of the study provide comparable data and practical tools for colour planning and management of urban historic building facades.http://www.sciencedirect.com/science/article/pii/S2095263525000081Colour perceptionImage clustering algorithmSubjective evaluationGuangzhou areaHierarchical structure |
| spellingShingle | Tianyi Fan Xiaoxiang Tang Kerun Li Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China Frontiers of Architectural Research Colour perception Image clustering algorithm Subjective evaluation Guangzhou area Hierarchical structure |
| title | Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China |
| title_full | Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China |
| title_fullStr | Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China |
| title_full_unstemmed | Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China |
| title_short | Image clustering algorithm and psychological perception in historical building colour rating research: A case study of Guangzhou, China |
| title_sort | image clustering algorithm and psychological perception in historical building colour rating research a case study of guangzhou china |
| topic | Colour perception Image clustering algorithm Subjective evaluation Guangzhou area Hierarchical structure |
| url | http://www.sciencedirect.com/science/article/pii/S2095263525000081 |
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