Automated Recognition of a Wall between Windows from a Single Image

Joint Authors

Huo, Linsheng
Li, Hong-Nan
Zhang, Yaowen

Source

Journal of Sensors

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

Civil Engineering

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