TY - GEN
T1 - Segmentation of characters on car license plates
AU - He, Xiangjian
AU - Zheng, Lihong
AU - Wu, Qiang
AU - Jia, Wenjing
AU - Samali, Bijan
AU - Palaniswami, Marimuthu
PY - 2008
Y1 - 2008
N2 - License plate recognition usually contains three steps, namely license plate detection/localization, character segmentation and character recognition. When reading characters on a license plate one by one after license plate detection step, it is crucial to accurately segment the characters. The segmentation step may be affected by many factors such as license plate boundaries (frames). The recognition accuracy will be significantly reduced if the characters are not properly segmented. This paper presents an efficient algorithm for character segmentation on a license plate. The algorithm follows the step that detects the license plates using an AdaBoost algorithm. It is based on an efficient and accurate skew and slant correction of license plates, and works together with boundary (frame) removal of license plates. The algorithm is efficient and can be applied in real-time applications. The experiments are performed to show the accuracy of segmentation.
AB - License plate recognition usually contains three steps, namely license plate detection/localization, character segmentation and character recognition. When reading characters on a license plate one by one after license plate detection step, it is crucial to accurately segment the characters. The segmentation step may be affected by many factors such as license plate boundaries (frames). The recognition accuracy will be significantly reduced if the characters are not properly segmented. This paper presents an efficient algorithm for character segmentation on a license plate. The algorithm follows the step that detects the license plates using an AdaBoost algorithm. It is based on an efficient and accurate skew and slant correction of license plates, and works together with boundary (frame) removal of license plates. The algorithm is efficient and can be applied in real-time applications. The experiments are performed to show the accuracy of segmentation.
UR - http://www.scopus.com/inward/record.url?scp=58049128306&partnerID=8YFLogxK
U2 - 10.1109/MMSP.2008.4665111
DO - 10.1109/MMSP.2008.4665111
M3 - Conference contribution
AN - SCOPUS:58049128306
SN - 9781424422951
T3 - Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008
SP - 399
EP - 402
BT - Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008
T2 - 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008
Y2 - 8 October 2008 through 10 October 2008
ER -