TY - GEN
T1 - Segmenting characters from license plate images with little prior knowledge
AU - Jia, Wenjing
AU - He, Xiangjian
AU - Wu, Qiang
PY - 2010
Y1 - 2010
N2 - In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.
AB - In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.
UR - http://www.scopus.com/inward/record.url?scp=79951642845&partnerID=8YFLogxK
U2 - 10.1109/DICTA.2010.48
DO - 10.1109/DICTA.2010.48
M3 - Conference contribution
AN - SCOPUS:79951642845
SN - 9780769542713
T3 - Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010
SP - 220
EP - 226
BT - Proceedings - 2010 Digital Image Computing
T2 - International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010
Y2 - 1 December 2010 through 3 December 2010
ER -