模型匹配是用於尋找與模板圖像匹配之圖像的技術，常用於一些
平面圖像處理中，並存在有許多變體。
本篇論文將利用雜湊函數探討模板匹配問題，文中演算過程使用
雜湊函數將圖形轉為2D 矩陣處理，並且雜湊函式具有旋轉和翻轉不變
性，最後透過檢查具有相同雜湊值圖像塊的方式，找出兩個圖像之間
所有完全相同的模板。並透過GPU 作進一步加速計算，透過實驗結果
可得知比起CPU 版本，本方法在GPU 上的速度可以提升25 倍。

Template Matching is a technique to identify the parts on an image or subsequences
of a sequence to match a predened template. It can be used in digital image
processing. There are many variations of the template matching problem.
In this thesis, we have presented a matrix-based template matching algorithm. The
algorithm utilizes a hash function to transform an image into a 2-D matrix. The
hash function is rotation and re
ection invariance. Then check the image blocks
that have the same hash values to identify all the exact same templates between
two images. And the method has implemented on GPU. The experimental results
show that the performance on GPU is accelerated approximately 25 times than the
CPU version.

Chinese Abstract i
Abstract ii
Contents iv
List of Figures vi
List of Tables vii
1 Introduction 1
2 Background 3
2.1 Template Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 GPU and CUDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.3 Related research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3 Methodology 8
3.1 Problem denition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.2 Algorithm description . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.3 Rotation invariant hashing . . . . . . . . . . . . . . . . . . . . . . . . 11
3.4 GPU implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4 Experiments 14
4.1 Computing time of each phase . . . . . . . . . . . . . . . . . . . . . . 14
4.2 Comparison between GPU and CPU . . . . . . . . . . . . . . . . . . 15
4.3 Comparison of Hash methods . . . . . . . . . . . . . . . . . . . . . . 15
4.4 Maximum hash value . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
4.5 Discussion for the k value . . . . . . . . . . . . . . . . . . . . . . . . 17
4.6 Template size and number . . . . . . . . . . . . . . . . . . . . . . . . 18
5 Conclusion 19

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