臺灣博碩士論文加值系統

在這篇論文中，我們結合了資料探戡和影像處理技術，協助我們找出影像中所隱藏的空間關係與資訊。為了找出這些資訊，我們提出一個影像探戡的架構：空間關聯法則，所謂空間關聯法則是用來描述影像中某個位置的內容與另一個位置的內容存有關聯性，我們提供了演算法來找出這些空間關聯法則。在應用方面，我們將空間關聯法則實作在影像分類上。我們找出自然景物照片中色彩的空間關連性，例用這些關聯法則來做新影像的分類。論文中的實驗結果可以顯示，利用色彩空間關聯法則來分類，準確度可以達到86%。

In this paper, we integrate data mining with image processing for discovering spatial relationships in images. We present an image mining framework, Spatial Association Rulemining (SAR), to mine spatial associations located in specific locations of images. A rule in the SAR refers to the occurrences of image content in a pair of spatial locations. The proposed approach is applied to mine color spatial association rules (color-SAR) in landscape scene images so as to demonstrate that the spatial association rules is able to the application of image classification. Our experimental results show that the classification accuracy of 86% can be achieved by the rule-based classifier.

1 Introduction 6
2 RelatedWork 12
3 Preliminaries 14
3.1 Algorithm Apriori 14
3.2 The Earth Mover''s Distance 17
4 Spatial Association Rule 19
4.1 Problem Formulation 19
4.2 Algorithm SAR-Mining 21
5 Application to Image Classification 28
5.1 Extraction of color items 29
5.2 Generation of color-SAR in each class 30
5.3 The image classifier 31
5.3.1 Distance Measurement 31
5.3.2 Classification of An Image 34
6 Experimental Results 37
6.1 Rule-based classifier 37
7 Conclusion 43

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