隨著科技進步和經濟起飛，開始使用車輛來代替步行的人越來越多。而在台灣地小人口又密集的情況下，發生了車位嚴重不足的情況。為了提高生活品質，很多人購買了相當高級的車種，也使得盜竊率往上攀升。因此，使監控系統能獲取即時資訊的議題探討受到相當大的重視。因此，本論文主要目的在於實現即時的車牌辨識系並驗證其結果。當中利用嵌入式系統與車牌辨識系統做結合，來達到即時性與低成本。內容分成硬體架構以及軟體演算法部分：硬體部分利用嵌入式系統來獲取影像來源和演算法運算。軟體演算法部分：車牌辨識系統主要分為車牌定位、字元切割、字元辨識等三大步驟。在車牌定位方面，本論文利用Gabor filter的特性來做影像增強，達到突顯車牌垂直邊緣的效果。在車牌測試方面，使用50張影像來源進行實驗，車牌定位率平均結果達98%，字元切割率平均結果達95%，字元辨識率平均結果達92%。

With the rapid development of technology and economy to take off，more and more people uses Vehicles to replace walking. There are small land and concentrated population in Taiwan, situation which parking are serious shortage happen. In order to improve quality of life, many people buy very advanced vehicles, render average accuracy of theft is ascent. Therefore, the questions which monitoring system can be captured real-time information suffer considerable attention. Therefore, the main purpose of this thesis is to achieve real-time license plate recognition system and verify the results. This thesis use embedded system to do with license plate recognition which achieves real-time and low cost. In this thesis, the system can be divided into hardware architecture and the software algorithm. In hardware, an embedded system is used to capture the image. In the software algorithm, three major steps in the license plate recognition system are addressed. First, license plate positioning, second, character segmentation, and third, character recognition. In license plate positioning, this thesis used features of the Gabor filter to carry out image enhancement based on the perpendicular edges, so that the positioning rate can be increased. In testing of license plate, we use the 50 source of image for the testing, the average accuracy of license plate positioning is 98%, the average accuracy of character segmentation is 95%, and the average accuracy of character recognition is 92%.

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