抄録
This paper describes the preceding vehicle recognition and road-lane recognition methods for the rear-end collision avoidance system (RCAS) which we are developing. These methods are using an edge histogram method based on modelbased vision. The edge histogram method can detect line elements of the objects stably with low calculation cost. When the region of interests for the preceding vehicle and road lanes in the image are established and their projected edge histograms are observed in time series order, we can recognize the positions of the vehicle and the lane. Furthermore, we apply Kalman Filter to their motions and predict their locations for time series detection. Using this stable recognition, we derive a collision time to control the on-board brake system. We show the performance of these methods by experimental results.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 327-332 |
| ページ数 | 6 |
| ジャーナル | IEEJ Transactions on Sensors and Micromachines |
| 巻 | 118 |
| 発行部数 | 6 |
| DOI | |
| 出版物ステータス | Published - 1998 |
| 外部発表 | Yes |
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ASJC Scopus subject areas
- Mechanical Engineering
- Electrical and Electronic Engineering
これを引用
An Approach to the Vehicle Tracking Method using Intensity Projection of the Edge Image. / Yamada, Kenichi; Ito, Toshio.
：: IEEJ Transactions on Sensors and Micromachines, 巻 118, 番号 6, 1998, p. 327-332.研究成果: Article
}
TY - JOUR
T1 - An Approach to the Vehicle Tracking Method using Intensity Projection of the Edge Image
AU - Yamada, Kenichi
AU - Ito, Toshio
PY - 1998
Y1 - 1998
N2 - This paper describes the preceding vehicle recognition and road-lane recognition methods for the rear-end collision avoidance system (RCAS) which we are developing. These methods are using an edge histogram method based on modelbased vision. The edge histogram method can detect line elements of the objects stably with low calculation cost. When the region of interests for the preceding vehicle and road lanes in the image are established and their projected edge histograms are observed in time series order, we can recognize the positions of the vehicle and the lane. Furthermore, we apply Kalman Filter to their motions and predict their locations for time series detection. Using this stable recognition, we derive a collision time to control the on-board brake system. We show the performance of these methods by experimental results.
AB - This paper describes the preceding vehicle recognition and road-lane recognition methods for the rear-end collision avoidance system (RCAS) which we are developing. These methods are using an edge histogram method based on modelbased vision. The edge histogram method can detect line elements of the objects stably with low calculation cost. When the region of interests for the preceding vehicle and road lanes in the image are established and their projected edge histograms are observed in time series order, we can recognize the positions of the vehicle and the lane. Furthermore, we apply Kalman Filter to their motions and predict their locations for time series detection. Using this stable recognition, we derive a collision time to control the on-board brake system. We show the performance of these methods by experimental results.
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UR - http://www.scopus.com/inward/citedby.url?scp=2442470927&partnerID=8YFLogxK
U2 - 10.1541/ieejsmas.118.327
DO - 10.1541/ieejsmas.118.327
M3 - Article
AN - SCOPUS:2442470927
VL - 118
SP - 327
EP - 332
JO - IEEJ Transactions on Sensors and Micromachines
JF - IEEJ Transactions on Sensors and Micromachines
SN - 1341-8939
IS - 6
ER -