臺灣博碩士論文加值系統

本文提出了一個以RGB 比值空間來表示色彩成分，即以RGB三成份對於參考顏色的比值來表示整張影像，不僅可消除亮度變化所造成的影響，更因保存了三色彩成分的資訊，對於彩度的表示，相較於HSI空間而言，保留了更完整的資訊。本文利用RGB比值之線性關係對於道路色彩模型進行建模，並以一橢圓形區域作為道路色彩模型的範圍，而決策系統則使用動態模糊邏輯，本文提出動態歸屬度函數範圍，使其在判定色彩相似度時，隨著所對應亮度的不同，而動態改變歸屬度函數範圍，讓決策系統具有更好的強健性與適應性。透過與現有方法的比較可顯現本文所提出之色彩分割方法能有效降低誤判率以及更能消除陰影及亮度變化所造成的影響。
本文更將模糊c均值分類演算法加以改良，使其應用於所提出之RGB比值色彩空間，除了將一般群聚的中心點以中心線代替外，更不需事先知道所需分類的群聚數目，利用此改良之分類法，針對道路偵測的應用上，成功克服因為陰影及反光所造成之偵測失誤。利用道路偵測所得之結果，透過Image-to-MIDI的資訊轉換，將其應用於盲人導行系統。其中物件遠近轉換為音量的大小，不同物件即以不同樂器表示，而物件的左右則以播放的順序來表示，由左至右播放。實驗結果顯示，本文所提出之轉換法則能有效的告知使用者障礙物的大小、方位及遠近，而本系統在計算時間的花費上，平均約200毫秒，約為5Hz，已達到一般行車導航的即時應用水準。

In this study, the RGB color ratio space is proposed and defined according to a reference color Different to traditional distance measurement, a road color model is determined by an ellipse area in the RGB ratio space enclosed by the estimated boundaries. A proposed dynamic fuzzy logic, which fuzzy membership functions are defined according to estimated boundaries, is introduced to implement clustering rules. Therefore, each pixel will have its own fuzzy membership function corresponding to its intensity. Fuzzy c-means line-clustering which integrate linear regression into fuzzy c-means method is introduced and applied on the RGB ratio space to overcome shadow and reflection problems. Comparing with the JSEG method, the proposed method is invariant to intensity variation and higher performance is achieved. To develop an image guidance system for visually impaired people, Image-to-MIDI mapping is introduced to transform image information into sound patterns. Experimental results show that the proposed method can be adapted to various road types and the resulting audio information successfully indicates obstacle position and size. As a result, the proposed approach is a great benefit to the study of road detection and image guidance systems.

ABSTRACT IN CHINESE i
ABSTRACT ii
ACKNOWLEDGMENT iii
CONTENTS iv
LIST OF TABLES vii
LIST OF FIGURES viii
NOMENCLATURE xi
CHAPTER I INTRODUCTION 1
1.1 Color Segmentation Methods 1
1.2 Road Detection Methods 6
1.3 Basic Image Processing Techniques 8
1.3.1 Edge Detection 8
1.3.2 Hough Transform 14
1.3.3 Vanishing Point and Vanishing Lines 17
1.4 Structure of the Dissertation 20
CHAPTER II RGB RATIO SPACE ＆ ROAD MODEL CONSTRUCTION 22
2.1 Conventional Color Spaces 22
2.1.1 RGB Color Space 22
2.1.2 CMY Color Space 23
2.1.3 CIE L*u*v* Space 24
2.1.4 HSI Color Space 25
2.2 RGB Ratio Space 29
2.3 Road Model Construction 33
CHAPTER III DYNAMIC FUZZY LOGIC COLOR SEGMENTATION 39
3.1 Fuzzy Logic 39
3.1.1 History of Fuzzy Logic 39
3.1.2 Fuzzy Sets 40
3.1.3 Fuzzy Set Shapes 42
3.1.4 Propositions 43
3.1.5 Fuzzification and Defuzzification 45
3.2 Dynamic Fuzzy Logic 50
3.2.1 Fuzzy Logic with Dynamic Membership Functions 50
3.2.2 Parameters Optimization with Neural Network 53
3.3 Road Segmented Results 58
CHAPTER IV FUZZY C-MEANS LINE-CLUSTERING 69
4.1 K-Means Clustering 69
4.2 Fuzzy c-Means Clustering 74
4.3 Fuzzy c-Means Line-Clustering 78
4.4 Segmented Results ＆ Comparisons 84
CHAPTER V IMAGE GUIDANCE SYSTEM FOR VISUALLY IMPAIRED PEOPLE 91
5.1 Audio Image Guidance Systems 91
5.2 Musical Instrument Digital Interface (MIDI) 94
5.2.1 Channel Messages 95
5.2.2 System Messages 99
5.3 Image-to-MIDI Mapping Algorithm 100
5.3.1 The Definition of Hot Zone 100
5.3.2 Obstacle Information Extraction 101
5.3.3 Image-to-MIDI Mapping Algorithm 104
5.4 Experimental Results 107
CHAPTER VI CONCLUSIONS 116
6.1 Conclusions 116
6.2 Suggestions for Future Researchers 118
REFERENCES 120
PUBLICATION LIST 127
VITA 129

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