Color Quality Evaluation of Urban Street Buildings Based on Artificial Intelligence and Street View Images: Taking Zhongshan Road Historical and Cultural Street in Shenyang as an Example

JiaNing Niu; Mei Lyu; MeiQi Yang; XiangQuan Wang

doi:10.2991/978-94-6463-266-8_38

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Color Quality Evaluation of Urban Street Buildings Based on Artificial Intelligence and Street View Images: Taking Zhongshan Road Historical and Cultural Street in Shenyang as an Example

Authors

JiaNing Niu¹, Mei Lyu¹^{, *}, MeiQi Yang¹, XiangQuan Wang¹

¹Shenyang Jianzhu University, ShenyangLiaoning, China

^*Corresponding author. Email: lymmei@sjzu.edu.cn

Corresponding Author

Mei Lyu

Available Online 10 October 2023.

DOI: 10.2991/978-94-6463-266-8_38 How to use a DOI?
Keywords: Historic streets; Building color quality; Python
Abstract: Historical and cultural streets not only are an important part of the urban historical context, but also show the urban memory. The color of the building facades in the historic and cultural streets greatly affects the visual quality of the environment. This study took the Zhongshan Road historical and cultural street in Shenyang as the site, and used Python to capture the street view image of buildings on both sides of a 1.7 km range within the Zhongshan Road historical and cultural street by Baidu Street View (BSV). At the same time, physical psychology were used to evaluate and analyze the Building Color Quality (BCQ), and further identified the existing problems and proposing optimization suggestions. It is helpful for planning and management of building colors in urban historical and cultural streets and provides constructive suggestions for the dynamic development of the urban areas.
Copyright: © 2024 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2nd International Conference on Intelligent Design and Innovative Technology (ICIDIT 2023)
Series: Atlantis Highlights in Intelligent Systems
Publication Date: 10 October 2023
ISBN: 978-94-6463-266-8
ISSN: 2589-4919
DOI: 10.2991/978-94-6463-266-8_38 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - JiaNing Niu
AU  - Mei Lyu
AU  - MeiQi Yang
AU  - XiangQuan Wang
PY  - 2023
DA  - 2023/10/10
TI  - Color Quality Evaluation of Urban Street Buildings Based on Artificial Intelligence and Street View Images: Taking Zhongshan Road Historical and Cultural Street in Shenyang as an Example
BT  - Proceedings of the 2nd International Conference on Intelligent Design and Innovative Technology (ICIDIT 2023)
PB  - Atlantis Press
SP  - 360
EP  - 369
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-266-8_38
DO  - 10.2991/978-94-6463-266-8_38
ID  - Niu2023
ER  -

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