| id |
caadria2016_703 |
| authors |
Ding, Yakui; Tomohiro Fukuda, Nobuyoshi Yabuki, Takashi Michikawa and Ali Motamedi |
| year |
2016 |
| title |
Automatic Measurement System of Visible Greenery Ratio Using Augmented Reality |
| source |
Living Systems and Micro-Utopias: Towards Continuous Designing, Proceedings of the 21st International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2016) / Melbourne 30 March–2 April 2016, pp. 703-712 |
| doi |
https://doi.org/10.52842/conf.caadria.2016.703
|
| summary |
Greening has been promoted to improve the living condi- tions in urban environments. Quantification of greenery is an im- portant issue to identify the criteria for stakeholders in the process of greening. This research focuses on the quantification of visible green- ery ratio which is defined as the amount of greenery in the field of vi- sion. Some measurement methods of visible greenery ratio have been already proposed. However, the quantification process is usually time consuming and prone to human errors due to manual operations by us- ing an image processing software. Therefore, in this research, the au- thors developed an automated measurement system based on image processing technology for the efficient visible greenery ratio meas- urement. In the verification experiment, the proposed method achieved similar results for extracted pixels of green areas as the tradi- tional manual method, with decreased calculation time. Furthermore, in addition to measuring the current ratio of greenery, this system can visualize possible future changes in visible greenery by adding plant- ing (landscape) design models in an Augmented Reality (AR) envi- ronment. Using the proposed method, an ideal greening environment can be designed and evaluated by end-users, more intuitively. The de- veloped design system is expected to eventually result in increasing the amount of greenery in the urban environment. |
| keywords |
Visible greenery ratio; image processing; automatic measurement tool; augmented reality |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (3,829,976 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:55 |
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