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系統識別號 U0026-0812200910224779
論文名稱(中文) 高維度統計資料分析與影像資料庫之搜尋技術
論文名稱(英文) A Fast Image Retrieval System Using High Order Fuzzy Statistics Model Parameters
校院名稱 成功大學
系所名稱(中) 資訊工程學系碩博士班
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 90
學期 2
出版年 91
研究生(中文) 吳信誠
研究生(英文) Shien-Cheng Wu
電子信箱 ashin@iie.ncku.edu.tw
學號 p7689107
學位類別 碩士
語文別 中文
論文頁數 66頁
口試委員 口試委員-王聖智
口試委員-孫永年
口試委員-鄭芳炫
口試委員-陳嘉琳
指導教授-蘇文鈺
中文關鍵字 影像分割  統計模型參數  直方統計圖  EM演算法  搜尋  索引 
英文關鍵字 image segmetation  indexing  histogram  searching 
學科別分類
中文摘要 由於現今是網路流通、資訊爆炸的時代,對於各種資料(網頁、文章、影像、音樂等)的需求量都很大,而且在要求尋找資料的速度要快速、搜尋結果要合乎使用者的需求,都是現代資料搜尋的趨勢。因此在資訊資料庫的建立與搜尋技術的研究上,在近幾年也有許許多多的研究與發展。
在影像的搜尋技術上,不外乎擷取影像的特徵,將所擷取出的特徵做處理(正規化、轉換特徵空間)成為另一種特徵表示法,利用所處理得到的特徵建立為影像的索引(index),最後依據建立的索引發展出合適的搜尋技術。代表影像的特徵通常由色彩、物體的外形輪廓、或者將影像做傅立葉轉換(fourier transform)、小波轉換(wave- let transform)取其轉換後的係數值作為特徵等。在本論文中利用影像的色彩資訊與影像中局部灰階值的統計特性作為影像的特徵,最後依據色彩資訊與統計特徵參數從影像資料庫中找到相似的影像。我們的系統分為三大部分:第一部份為色彩影像分割(color image segmentation),利用顏色在影像中的分布情形將分割影像為若干小區域,而每個區域具有相似的色彩分布,並記錄其中色彩區域的顏色分佈值與佔有比例。第二部份為影像內容的統計模型估計,並記錄下統計模型的參數值。第三部份為影像相似度的判別,我們根據前兩部分所獲得的資訊作為判斷影像相似的根據,可以由色彩主導、影像內容統計特性主導、或是結合兩特徵做二階層式(2-level)搜尋的結果顯示。

英文摘要 With the growing sizes of today’s digital image database, fast retrieval methods are mandatory. Though shape and color are the most popular features in many retrieval systems, it is possible that other abstract representations can also be used to extract additional useful information for this application. For example, quite a few high order statistics methods were successfully used in texture image classification. In this paper, we present a fast retrieval system using a maximally simplified fuzzy parametrical statistic representation and a color region representation, and combine them be with a 2-level matching strategy based on an input reference image. The proposed statistics model is used to explore the spatial relationship among the neighboring image pixels. Among the retrieval images, some of them are highly related to the input reference image even in a human point of view.

論文目次 英文摘要i
中文摘要ii
致 謝iii
目 錄iv
表 目 錄vi
圖 目 錄vii
符 號x

1 研究動機與目的1
1.1研究動機1
1.2研究目的3
2 色彩影像分割技術(Color Image Segmentation Technique)5
2.1同質特徵(Homogeneity Feature)5
2.2直方統計圖分析方法(Histogram Analysis)9
2.3色彩特徵分析(Color Feature Analysis)13
3 高維度機率統計模型18
3.1統計模型估測方法之介紹18
3.2直方統計圖法與核心估計法(Histograms and Kernel Estimates)23
3.3以分群為基礎的機率估計法(Cluster-Based Probability Estimation)25
3.3.1分群分析法:K-means Algorithm 25
3.3.2 EM演算法的簡介 27
3.3.3調整統計模型參數經由EM演算法 29
4 影像比對與搜尋技術 34
4.1影像特徵索引(Image Feature Indexing) 34
4.1.1色彩特徵索引(Color Feature Indexing) 34
4.1.2統計特徵索引(Statistical Feature Indexing) 35
4.2影像比對與搜尋 38
4.2.1影像特徵比對(Similarity Measure) 39
4.2.2影像搜尋(Searching) 41
5 實驗結果討論 45
5.1系統實作(System Implementation) 45
5.2實驗結果比較(Experimental Result Comparison) 46
5.2.1依不同搜尋條件的搜尋結果比較 47
5.2.2從第一層搜尋後選取不同影像張數作第二層搜尋的搜尋結果比較 58
5.3實驗效能討論 60
6 結論與未來發展方向 62
參考文獻 64
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