TY - GEN
T1 - Suspected vehicle detection for driving without license plate using symmelets and edge connectivity
AU - Hsieh, Jun-Wei
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/20
Y1 - 2017/10/20
N2 - This paper proposes a novel suspected vehicle detection (SVD) system for detecting vehicles moving on roads without a license plate. To detect vehicles from a still image, a symmelet-based approach is derived to determine their ROIs without using any motion feature. A symmelet is a pair of an interest point and its corresponding symmetrical one. This paper modifies the non-symmetrical SURF descriptor into a symmetrical one without adding any time complexity. Then, different symmelets can be very efficiently extracted from road scenes. The set of symmelets can be then used to locate the desired vehicle's ROI using a projection technique. To examine whether a license plate exists within this ROI, an edge connectivity scheme is then proposed to highlight possible character regions for plate detection. This SVD system provides two advantages; there is no need of background subtraction and it is extremely efficient for real-time ITS applications without using any GPU.
AB - This paper proposes a novel suspected vehicle detection (SVD) system for detecting vehicles moving on roads without a license plate. To detect vehicles from a still image, a symmelet-based approach is derived to determine their ROIs without using any motion feature. A symmelet is a pair of an interest point and its corresponding symmetrical one. This paper modifies the non-symmetrical SURF descriptor into a symmetrical one without adding any time complexity. Then, different symmelets can be very efficiently extracted from road scenes. The set of symmelets can be then used to locate the desired vehicle's ROI using a projection technique. To examine whether a license plate exists within this ROI, an edge connectivity scheme is then proposed to highlight possible character regions for plate detection. This SVD system provides two advantages; there is no need of background subtraction and it is extremely efficient for real-time ITS applications without using any GPU.
UR - http://www.scopus.com/inward/record.url?scp=85039921812&partnerID=8YFLogxK
U2 - 10.1109/AVSS.2017.8078467
DO - 10.1109/AVSS.2017.8078467
M3 - Conference contribution
AN - SCOPUS:85039921812
T3 - 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
BT - 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
Y2 - 29 August 2017 through 1 September 2017
ER -