The Research for License Plate Recognition using Sub-Image Fast Independent Component Analysis
In order to solve the problem that current license plate recognition methods, such as template matching and neural network computing, which need a large number of samples and large amount of computation, this paper proposed a sub-image fast independent component analysis (SI-FastICA) method for plate recognition. It can obtain the local feature of the image with a small amount of computation. In order to obtain better recognition results, in the stage of character segmentation, this paper carried segmentation based on the proposed relative coordinate dichotomy. Then, the feature of characters was extracted by SI-FastICA. The experiments show that SI-FastICA can reflect the local characteristics of the character very well. At last, this paper put the collected actual license plate images into experiment, and achieved good recognition results.
plate recognition fast independent component analysis character segmentation difference projection
Jian W. Fang Wei S. Yang Hong K. Xu
School of Electronic and Control Engineering, Chang’an University, Xi’an, 710064, PRC
国际会议
2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
四川绵阳
英文
1915-1920
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）