TY - GEN
T1 - Real-time detection of vehicles for advanced traffic signal control
AU - Han, Chong
AU - Zhang, Qinyu
PY - 2008
Y1 - 2008
N2 - Vehicle detection by video cameras is one of the most promising new technologies for wireless large-scale data collection and implementation of advanced traffic control and management schemes such as vehicle guidance/navigation. In this paper we propose an approach to detect and count vehicles at an intersection in real-time, using a fixed camera. After identifying moving objects images via background frame differencing, edge detection, erosion and dilation operations are performed to suppress noise. Separated and rotated properly, the denoised binary image is then used to generate a vertical projection histogram from which information about the size and coordinates of each component is utilized to compute the number of vehicles. This detection algorithm gives an approximate number of vehicles. An adaptive traffic signal control strategy controls the traffic flow. The simulating results show a great efficiency of traffic control and management scheme in practice.
AB - Vehicle detection by video cameras is one of the most promising new technologies for wireless large-scale data collection and implementation of advanced traffic control and management schemes such as vehicle guidance/navigation. In this paper we propose an approach to detect and count vehicles at an intersection in real-time, using a fixed camera. After identifying moving objects images via background frame differencing, edge detection, erosion and dilation operations are performed to suppress noise. Separated and rotated properly, the denoised binary image is then used to generate a vertical projection histogram from which information about the size and coordinates of each component is utilized to compute the number of vehicles. This detection algorithm gives an approximate number of vehicles. An adaptive traffic signal control strategy controls the traffic flow. The simulating results show a great efficiency of traffic control and management scheme in practice.
UR - https://www.scopus.com/pages/publications/62949241239
U2 - 10.1109/ICCEE.2008.126
DO - 10.1109/ICCEE.2008.126
M3 - 会议稿件
AN - SCOPUS:62949241239
SN - 9780769535043
T3 - Proceedings of the 2008 International Conference on Computer and Electrical Engineering, ICCEE 2008
SP - 245
EP - 249
BT - Proceedings of the 2008 International Conference on Computer and Electrical Engineering, ICCEE 2008
T2 - 2008 International Conference on Computer and Electrical Engineering, ICCEE 2008
Y2 - 20 December 2008 through 22 December 2008
ER -