Abstract
The proposal of this study is introducing a new feature, called soft Histogram of Oriented Gradients (SHOG). This feature is designed for traffic sign detection. SHOG differs from traditional (hard) HOG in terms of symmetry information and cell of histogram positions. Unlike hard HOG, SHOG changes the positions of cells to a randomized selection of cells following by symmetry shapes of the traffic sign images. SHOG is implemented on the famous German traffic sign detection benchmark (GTSDB) dataset. Comparing to the conventional HOG feature experimented on GTSDB, SHOG could show better performance while uses smaller feature size.
| Original language | English |
|---|---|
| Title of host publication | 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 388-392 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509008216 |
| DOIs | |
| Publication status | Published - 2016 Oct 21 |
| Event | 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 - Xian, China Duration: 2016 Aug 19 → 2016 Aug 22 |
Other
| Other | 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016 |
|---|---|
| Country | China |
| City | Xian |
| Period | 16/8/19 → 16/8/22 |
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All Science Journal Classification (ASJC) codes
- Modelling and Simulation
- Artificial Intelligence
- Control and Optimization
Cite this
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Application of soft Histogram of Oriented Gradient on traffic sign detection. / Kassani, Peyman Hosseinzadeh; Hyun, Junhyuk; Kim, Euntai.
2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 388-392 7734067.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Application of soft Histogram of Oriented Gradient on traffic sign detection
AU - Kassani, Peyman Hosseinzadeh
AU - Hyun, Junhyuk
AU - Kim, Euntai
PY - 2016/10/21
Y1 - 2016/10/21
N2 - The proposal of this study is introducing a new feature, called soft Histogram of Oriented Gradients (SHOG). This feature is designed for traffic sign detection. SHOG differs from traditional (hard) HOG in terms of symmetry information and cell of histogram positions. Unlike hard HOG, SHOG changes the positions of cells to a randomized selection of cells following by symmetry shapes of the traffic sign images. SHOG is implemented on the famous German traffic sign detection benchmark (GTSDB) dataset. Comparing to the conventional HOG feature experimented on GTSDB, SHOG could show better performance while uses smaller feature size.
AB - The proposal of this study is introducing a new feature, called soft Histogram of Oriented Gradients (SHOG). This feature is designed for traffic sign detection. SHOG differs from traditional (hard) HOG in terms of symmetry information and cell of histogram positions. Unlike hard HOG, SHOG changes the positions of cells to a randomized selection of cells following by symmetry shapes of the traffic sign images. SHOG is implemented on the famous German traffic sign detection benchmark (GTSDB) dataset. Comparing to the conventional HOG feature experimented on GTSDB, SHOG could show better performance while uses smaller feature size.
UR - http://www.scopus.com/inward/record.url?scp=85000702963&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85000702963&partnerID=8YFLogxK
U2 - 10.1109/URAI.2016.7734067
DO - 10.1109/URAI.2016.7734067
M3 - Conference contribution
AN - SCOPUS:85000702963
SP - 388
EP - 392
BT - 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -