Abstract
Aerial images are available in recent days. They are useful to observe the aging of the city. However, it's difficult to extract the significant spatial information from them. Many features in the city make it difficult to analyze spatial information by visual observation. In this paper, we propose two methods. One is a method to detect roof domains from aerial images using Multi-Level Slice classification. The other is a method which detects city geographical feature change automatically. In this paper, we run an experiment to verify the accuracy of our method and show the results.
| Original language | English |
|---|---|
| Pages (from-to) | 25-29 |
| Number of pages | 5 |
| Journal | Journal of the Institute of Image Electronics Engineers of Japan |
| Volume | 42 |
| Issue number | 1 |
| Publication status | Published - 2013 |
Fingerprint
Keywords
- Aerial Image
- Building detection
- Change detection
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Electrical and Electronic Engineering
Cite this
Building detection and change detection using aerial images. / Nakamura, Satoshi; Aoki, Yoshimitsu.
In: Journal of the Institute of Image Electronics Engineers of Japan, Vol. 42, No. 1, 2013, p. 25-29.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Building detection and change detection using aerial images
AU - Nakamura, Satoshi
AU - Aoki, Yoshimitsu
PY - 2013
Y1 - 2013
N2 - Aerial images are available in recent days. They are useful to observe the aging of the city. However, it's difficult to extract the significant spatial information from them. Many features in the city make it difficult to analyze spatial information by visual observation. In this paper, we propose two methods. One is a method to detect roof domains from aerial images using Multi-Level Slice classification. The other is a method which detects city geographical feature change automatically. In this paper, we run an experiment to verify the accuracy of our method and show the results.
AB - Aerial images are available in recent days. They are useful to observe the aging of the city. However, it's difficult to extract the significant spatial information from them. Many features in the city make it difficult to analyze spatial information by visual observation. In this paper, we propose two methods. One is a method to detect roof domains from aerial images using Multi-Level Slice classification. The other is a method which detects city geographical feature change automatically. In this paper, we run an experiment to verify the accuracy of our method and show the results.
KW - Aerial Image
KW - Building detection
KW - Change detection
UR - http://www.scopus.com/inward/record.url?scp=84902184555&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902184555&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84902184555
VL - 42
SP - 25
EP - 29
JO - Journal of the Institute of Image Electronics Engineers of Japan
JF - Journal of the Institute of Image Electronics Engineers of Japan
SN - 0285-9831
IS - 1
ER -