An Efficient Approach for Slant Correction of Vehicle Licenses Based on Hough Transform and Mathematics Morphology

In a real Vehicle License Plate Recognition System, the license images obtained by vidicon are usually slantwise. The slant of vehicle licenses will do harm to the Character Segment and Recognition. The paper advances a new method combining Hough Transform and Mathematics Morphology by the analysis of the vehicle licenses' slant pattern and the interference characteristics. Compared with the conventional methods, it overcomes the perplexity that too many disturbed lines and imperfect detection criterions. The experimental results show that the proposed method can improve the accuracy of the slant correction. It is confirmed that the noise immunity of the method is excellent, and the performance is robust. The correction rate of the newly developed algorithm has reached over 95%.