Yakui Ding, T. Fukuda, N. Yabuki, T. Michikawa, A. Motamedi
{"title":"Automatic Measurement System of Visible Greenery Ratio Using Augmented Reality","authors":"Yakui Ding, T. Fukuda, N. Yabuki, T. Michikawa, A. Motamedi","doi":"10.52842/conf.caadria.2016.703","DOIUrl":null,"url":null,"abstract":"Greening has been promoted to improve the living conditions in urban environments. Quantification of greenery is an important issue to identify the criteria for stakeholders in the process of greening. This research focuses on the quantification of visible greenery ratio which is defined as the amount of greenery in the field of vision. 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 using an image processing software. Therefore, in this research, the authors developed an automated measurement system based on image processing technology for the efficient visible greenery ratio measurement. In the verification experiment, the proposed method achieved similar results for extracted pixels of green areas as the traditional 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 planting (landscape) design models in an Augmented Reality (AR) environment. Using the proposed method, an ideal greening environment can be designed and evaluated by end-users, more intuitively. The developed design system is expected to eventually result in increasing the amount of greenery in the urban environment.","PeriodicalId":281741,"journal":{"name":"CAADRIA proceedings","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CAADRIA proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52842/conf.caadria.2016.703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Greening has been promoted to improve the living conditions in urban environments. Quantification of greenery is an important issue to identify the criteria for stakeholders in the process of greening. This research focuses on the quantification of visible greenery ratio which is defined as the amount of greenery in the field of vision. 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 using an image processing software. Therefore, in this research, the authors developed an automated measurement system based on image processing technology for the efficient visible greenery ratio measurement. In the verification experiment, the proposed method achieved similar results for extracted pixels of green areas as the traditional 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 planting (landscape) design models in an Augmented Reality (AR) environment. Using the proposed method, an ideal greening environment can be designed and evaluated by end-users, more intuitively. The developed design system is expected to eventually result in increasing the amount of greenery in the urban environment.