Automated Recognition of a Wall between Windows from a Single Image
Joint Authors
Huo, Linsheng
Li, Hong-Nan
Zhang, Yaowen
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-03
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
To avoid the time-consuming, costly, and expert-dependent traditional assessment of earthquake damaged structures, image-based automatic methods have been developed recently.
Since automated recognition of structure elements is the basis by which these methods achieve automatic detection, this study proposes a method to recognize the wall between windows from a single image automatically.
It begins from detection of line segments with further selection and linking to obtain longer line segments.
The color features of the two sides of each long line segment are employed to pick out line segments as candidate window edges and then label them.
Finally, the images are segmented into several subimages, window regions are located, and then the wall between the windows is located.
Real images are tested to verify the method.
The results indicate that walls between windows can be successfully recognized.
American Psychological Association (APA)
Zhang, Yaowen& Huo, Linsheng& Li, Hong-Nan. 2017. Automated Recognition of a Wall between Windows from a Single Image. Journal of Sensors،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1187274
Modern Language Association (MLA)
Zhang, Yaowen…[et al.]. Automated Recognition of a Wall between Windows from a Single Image. Journal of Sensors No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1187274
American Medical Association (AMA)
Zhang, Yaowen& Huo, Linsheng& Li, Hong-Nan. Automated Recognition of a Wall between Windows from a Single Image. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1187274
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187274