Abstract
This paper proposes the corner point detection algorithm which uses extreme value from Gray Level image. There are various methods to detect corner point. Corner point includes information about the length and shape of model. Preprocessing step is required to detect corner point. First, the model image is converted to gray-level image. After removing noise from converted image, edge lines are detected by edge detection algorithm. Existing SUSAN algorithm detects edge line by using area, but also detects wrong corner points. But proposed extreme value method only detects corner point which belongs to the defined area, so detection ratio can be increased. Proposed method can be used to detect model's exact displacement or to perform 3-D reconstruction.
| Original language | English |
|---|---|
| Title of host publication | ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings |
| Pages | 5392-5396 |
| Number of pages | 5 |
| Publication status | Published - 2009 Dec 1 |
| Event | ICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan Duration: 2009 Aug 18 → 2009 Aug 21 |
Other
| Other | ICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 |
|---|---|
| Country | Japan |
| City | Fukuoka |
| Period | 09/8/18 → 09/8/21 |
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Keywords
- Corner detection
- Corner point
- Extreme value
- Susan
ASJC Scopus subject areas
- Information Systems
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
Cite this
An improved corner point detection using extreme value of Susan method for measuring a displacement. / Jeon, Byung Seung; Woo, Dong Gi; Mo, Young Hak; Lim, Myo Taeg.
ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings. 2009. p. 5392-5396 5333226.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An improved corner point detection using extreme value of Susan method for measuring a displacement
AU - Jeon, Byung Seung
AU - Woo, Dong Gi
AU - Mo, Young Hak
AU - Lim, Myo Taeg
PY - 2009/12/1
Y1 - 2009/12/1
N2 - This paper proposes the corner point detection algorithm which uses extreme value from Gray Level image. There are various methods to detect corner point. Corner point includes information about the length and shape of model. Preprocessing step is required to detect corner point. First, the model image is converted to gray-level image. After removing noise from converted image, edge lines are detected by edge detection algorithm. Existing SUSAN algorithm detects edge line by using area, but also detects wrong corner points. But proposed extreme value method only detects corner point which belongs to the defined area, so detection ratio can be increased. Proposed method can be used to detect model's exact displacement or to perform 3-D reconstruction.
AB - This paper proposes the corner point detection algorithm which uses extreme value from Gray Level image. There are various methods to detect corner point. Corner point includes information about the length and shape of model. Preprocessing step is required to detect corner point. First, the model image is converted to gray-level image. After removing noise from converted image, edge lines are detected by edge detection algorithm. Existing SUSAN algorithm detects edge line by using area, but also detects wrong corner points. But proposed extreme value method only detects corner point which belongs to the defined area, so detection ratio can be increased. Proposed method can be used to detect model's exact displacement or to perform 3-D reconstruction.
KW - Corner detection
KW - Corner point
KW - Extreme value
KW - Susan
UR - http://www.scopus.com/inward/record.url?scp=77951141107&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951141107&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77951141107
SN - 9784907764333
SP - 5392
EP - 5396
BT - ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
ER -