A Robust License-Plate Extraction Method under Complex Image Conditions
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
License Plate Extraction in Low Resolution Video
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
An Efficient Features - Based License Plate Localization Method
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Robust License Plate Detection Using Covariance Descriptor in a Neural Network Framework
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
Region-based license plate detection
Journal of Network and Computer Applications
Real-Time license plate detection under various conditions
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
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This paper presents a novel texture descriptor based on line-segment features for text detection in images and video sequences, which is applied to build a robust car license plate localization system.Unlike most of existing approaches which use low level features (color, edge) for text / non-text discrimination, our arm is to exploit more accurate perceptual information. A - scale and rotation invariant - texture descriptor which describes the directionality, regularity, similarity, alignment and connectivity of group of segments are proposed. A improved algorithm for feature extraction based on local connective Hough transform has been also investigated.The robustness of our approach is proved throughout a real-time detection / verification scheme of car license plate. First, all possible candidates are detected using a rule based method, which is very robust to illumination change and in varying poses. Then, true license plates are identified by the mean of a SVM classifier trained with proposed descriptor. Comparison and evaluation are conducted with two complex datasets.