期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2009
卷号：9
期号：1
页码：54-61
出版社：International Journal of Computer Science and Network Security
摘要：A novel Pattern Accumulated Vector(PAV) method implemented by CAM-based architecture has been proposed for character recognition in license plate recognition(LPR). Instead of comparing all the pattern blocks, the PAV method adopts the principal pattern blocks as feature vectors so that the computation complexity is highly reduced. Furthermore, the PAV method adopts the extended templates for the character recognition and is proved to have higher recognition rate when dealing with license plates consisting inclined characters. Finally, the CAM architecture is used to further reduce the processing time and makes the PAV method more efficient for real-time LPR systems.
关键词：Content Addressable Memory(CAM); Pattern Accumulated Vector(PAV); License Plate Recognition(LPR); Character Recognition; principal pattern blocks
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