| Summary: | 碩士 === 國立臺灣科技大學 === 電子工程系 === 101 === Recently, parking lots were built everywhere, demand for road surveillance, and Taiwan distance-based toll system also needs to obtain a license plate number for the auxiliary mechanism, the License Plate Recognition (LPR) becomes a very important technology. In this study, the LPR technology was divided into image preprocessing, license plate location, character segmentation and character recognition. In the image preprocessing, does grayscale of image, reduces in size in order to improve the processing efficiency, and goes with histogram equalization and noise filter to increase the reliability. In license plate location, using Prewitt edge detector, dilation, and Connected Components Labeling method to get the candidate of license plate location. In character segmentation, makes the image binarization and does tilt detection and correction. Filters the interfered plate screws, does characters capture, and estimates those not found character position, to get all the character positions. In character recognition, forces normalization on characters, and does classification according to SOM and LVQ neural networks. In order to obtain better results, distinguishes parts of ambiguous characters. In the first implementation, practiced image processing and neural networks by using Matlab. Finally, ported the LPR algorithms to TI TMS320DM6446 DSP platform to achieve a real product.
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