臺灣博碩士論文加值系統

眼睛是人臉重要的特徵之一，並且在相當多的應用當中扮演著重要的角色；諸如：人臉檢測、人臉識別、情緒分析或是目視方向追蹤系統等。本文作者提出以眼睛區域上的線段色彩序列（Line Color Sequence, LCS）特徵作為檢測的依據，演算法除了著重在像素顏色的判斷，也致力於色彩序列的決策工作。相較以往檢測技術，不需先行定位人臉區域是主要的特色。搭配模糊自動機（Fuzzy Automata）建構LCS特徵擷取過程的模型，開發出低運算量的人眼檢測架構。

Eyes are one of the most important facial features and eyes detection play a quite important role in many useful applications, such as face detection, face recognition, facial expression analysis, or eye-gaze tracking systems. In this paper, the authors introduced an eye localization system based on the line color sequence (LCS) in the color images. The algorithm not only focuses on the identification of color types, but also engages in determining the spatial relationships between the colors. The novelty of this work is that the algorithm works without complete face location. With the fuzzy automata support, the lower mathematical computation is the advantage of our proposed method.

摘 要 II
ABSTRACT III
致謝 IV
目錄 V
圖索引 VIII
表索引 XI
第1章 簡介 11
1.1 研究背景 11
1.2 研究動機 3
1.3 研究大綱 3
1.4 論文架構 5
第2章 文獻探討 7
2.1 人眼檢測 7
2.1.1 基於模板（TEMPLATE-BASED） 7
2.1.2 基於整體表徵（APPEARANCE-BASED） 10
2.1.3 基於特徵（FEATURE-BASED） 11
2.2 人臉檢測 11
2.3 色彩空間與膚色分佈 13
2.3.1. RGB 13
2.3.2. NCC 13
2.3.3. HSV 14
2.3.4. YCBCR 14
2.4 膚色模型 16
2.4.1 膚色分佈範圍 16
2.4.2 非參數式模型(NON-PARAMETRIC) 18
2.4.3 參數式模型(PARAMETRIC) 19
2.5 細胞自動機（CELLULAR AUTOMATA） 21
2.5.1 有限自動機（FINITE AUTOMATA） 24
2.5.2 模糊有限自動機（FUZZY FINITE AUTOMATA，FFA） 25
第3章 研究架構 27
3.1 色彩空間轉換 28
3.2 像素色彩判斷 34
3.2.1 膚色像素判斷 34
3.2.2 眼白像素判斷 35
3.2.3 虹膜像素判斷 36
3.2.4 虹膜缺口補償 39
3.3 線色彩序列（LINE COLOR SEQUENCE-LCS）模糊自動機 41
3.3.1 LCS模糊自動機的建立 41
3.4 虹膜區域判斷 48
第4章 系統實作 51
4.1 實驗環境 51
4.2 影像資料庫 51
4.2.1 AR DATABASE 51
4.2.2 CALTECH DATABASE 52
4.2.3 ST. JOHN'S DATABASE 52
4.3 實驗結果 53
4.4 性能比較 62
第5章 結論與未來方向 65
參考文獻 66

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