| Summary: | 碩士 === 中原大學 === 電子工程研究所 === 93 === This thesis proposes a license plate recognition system for moving vehicles on the road. The system includes the following subsystems: motion edge detection, image extraction of moving vehicles, license plate locating, tilt plate correction, character segmentation and recognition. Motion edges are detected by calculating the image difference between adjacent frames. If enough amount of difference is detected, moving vehicles are assumed in the frames and the license plate locating procedure is activated. The license plate could be identified by finding vertical and horizontal projections in the area with highly concentrated edge densities to find out the precise location of the license plate. A connected component approach is used to extract characters from the license plate. If characters look blurring, we use low pass and sharpening filters to maintain the integrity of characters. In the character recognition part, we take the Back-Propagation Neural (BPN) Network as our principle method, and Self-Organized Map (SOM) as the auxiliary method. They are combined through a voting mechanism. In this way, we could achieve better recognition performance.
The experimental results show that the accuracy on character segmentation is 95%. On the overall recognition rate of the license plate, using BPN alone is 81.33%, and using the composite classifier integrating BPN and SOM is 90.78%. This result proves the effectiveness of the multi recognition system. Finally, the computation time to perform the recognition tasks for an image containing license plate, running on a P4 2.8G computer, is 0.3~0.5 seconds on the average.
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