臺灣博碩士論文加值系統

本論文介紹一個處理紋路分析的新方法，叫做紋路特徵編碼法。它結合灰階明亮度相互關係矩陣及紋路頻譜的優點。根據紋路特徵編碼法所產生的紋路特徵數統計圖及紋路特徵數相互關係矩陣可以導出許多紋路特徵。在實驗中我們將這個方法與灰階明亮度相互關係矩陣、紋路頻譜，和交叉－對角線紋路矩陣等三種紋路分析方法進行比較，以了解紋路特徵編碼法在分辨紋路影像方面的效能。從實驗結果可知紋路特徵編碼法比較其他三種紋路分析方法，有較佳的正確性且較不易受影像旋轉的影響。

This paper introduces a new texture analysis method named Texture Feature Coding Method (TFCM). This method incorporates with the merits of both the gray-level co-occurrence matrix (GLCM) and texture spectrum (TS) methods. The texture feature number histogram and the texture feature number co-occurrence matrix are generated by TFCM for derived many useful texture feature descriptors. Three texture analysis methods, GLCM, TS, and cross-diagonal texture matrix (CDTM), are used to compare and evaluate the performance with TFCM in discriminating some of Brodatz’s natural textures. The experimental results reveal that the TFCM is superior to other three methods in classification of natural textures, especially in classification of rotated textures.

目錄
書名頁 i
論文口試委員審定書 ii
論文指導教授推薦函 iii
授權書 iv
中文摘要 v
英文摘要 vi
誌謝 vii
目錄 viii
表目錄 x
圖目錄 xi
第一章　導論………………………………………………………...1
第1.1節　研究背景 1
第1.2節　研究目的 2
第1.3節　論文架構 2
第二章　背景知識…………………………………………………...3
第2.1節　紋路影像 3
第2.2節　紋路分析 6
第2.3節　紋路特徵 7
第2.4節　紋路辨別 8
第三章　相關方法……………………………………………….....10
第3.1節　灰階明亮度相互關係矩陣 10
第3.2節　紋路頻譜 19
第3.3節　交叉－對角線紋路矩陣 26
第四章　紋路特徵編碼法………………………………………….36
第4.1節　紋路特徵數的產生 36
第4.2節　紋路特徵數統計圖與紋路特徵數相互關係矩陣 42
第4.3節　計算紋路特徵數的例子 46
第4.4節　紋路特徵計算 49
第五章　實驗結果………………………………………………….52
第5.1節　紋路特徵數統計圖的分辨效能 54
第5.2節　紋路特徵的分辨效能 59
第六章　結論……………………………………………………….62
參考文獻 63

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