本研究係使用超解析影像重建( Super Resolution )，解決車牌辨識系統中低解析度( Low Resolution )車牌的辨識問題。然而，超解析影像重建的過程之中有一個很重要的環節，那就是影像的定位資訊。在相同的影像重建方法之下，有較佳的影像定位結果，相對的就會有較好的重建結果，因此我們可以瞭解到定位資訊的重要性。
　　常見的影像定位方法主要分為兩類，特徵法與區域法。特徵法係先找出特徵點，並利用特徵點求出定位資訊。而區域法則是運用圖片中大部分的區域作為計算定位的依據。吾人將設計一張最小位移單位為0.1個像素，及最小旋轉單位為0.1度之實驗影像。本研究利用此樣本測試文獻中所提之區域法和特徵法，吾人另外提出改善特徵法的方式，並試圖找出定位精度較高的定位方法。本研究最後將利用較精準之定位方法，並運用此方法所求出之定位結果做低解析車牌影像重建，試圖從難以辨別之低解析車牌資訊辨別出其車牌號碼。

In this paper, we use Super-resolution to save the problem of low resolution image in license plate recognition system. Image registration is an important part of image enhancement. In the same algorithm of the image enhancement, a precise sub-pixel image registration has a better result of image reconstruction. So, we can understand the important of the image registration.
There are two kinds of methods for image registration. One of the methods is feature based, the other is area based. The method of feature based finds control point first and finds the orientation of image by using control point. The method of area based finds the orientation of image by almost all over the range of image. We will design an image which's minimum shifted pixel is 0.1 pixel and minimum rotated angle is 0.1 degree. In this paper, we will find the best method of image registration in the biblliography by using the images which we designed. We also propose a new method to improve the method of feature based. We will recognition the low resolution license plate image by using the best method of image registration and try to find the information of the license plate image.

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