臺灣博碩士論文加值系統

隨著科技進步日新月異，電腦運算速度的倍增，許多以往因運算複雜度而不能被實現的技術現今已能化為實際的應用，尤其在人機介面上的長足進步，使得人們使用電腦更為簡單容易，如指紋辨識、聲紋辨識、手寫輸入和虹膜辨識等技術，讓我們能更輕鬆的接觸電腦。但人臉在相關的應用上一直無法達到實用的境地，這其中最大的因素就是沒能有一個準確可靠的人臉偵測技術，一個準確的人臉偵測技術能使得許多的應用被實現，如人臉辨識、表情辨識、安全監視系統、view morphing 等。這篇論文提出了一個新的方法來偵測眼睛的候選點，利用人臉的相關特徵並結合糢糊理論推論的方法來達到人臉偵測的目標。介由本論文所提出的偵測方法，我們可以得到人臉精確的位置、傾斜的角度、人臉的大小、兩眼的位置…等等的資訊，這些資訊將能很輕易的作更進一步的應用。

With the improvement of science and technology, the usage of human-machine interface is more popular and convenient in the recent years. A fast and accu-rate face detection approach is important for several applications, such as face recognition, security system, human-machine interface and TV-conference,etc.
This thesis proposes a new method to detect human eyes and uses feature-based approach with fuzzy logic theorem for face candidates confirmation. According to this detecting scheme, we can obtain the face location, face tilt angle, face size and predict the distance between a human and the camera.
These information are very useful for further applications.

Table of Contents i
List of Tables iii
List of Figures iv
Abstract(English) i
Abstract(Chinese) i
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Guide of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Literature Survey 4
3 Human Face Detection System 7
3.1 System Architecture . . . . . . . . . . . . . . . . . . . . . . . 7
3.2 Human Skin Color Distribution . . . . . . . . . . . . . . . . . 8
3.2.1 Perceptually Uniform Color Space . . . . . . . . . . . . 8
3.2.2 Building The Skin Color Model . . . . . . . . . . . . . 10
3.3 Crossing-Filter Eyes Detection . . . . . . . . . . . . . . . . . . 11
3.4 Feature-Based Face Detection Approach . . . . . . . . . . . . 14
3.4.1 Face Candidates . . . . . . . . . . . . . . . . . . . . . . 14
3.4.2 Eyes Feature Information . . . . . . . . . . . . . . . . 16
3.4.3 Mouth Feature . . . . . . . . . . . . . . . . . . . . . . 18
3.4.4 Cheeks Feature . . . . . . . . . . . . . . . . . . . . . . 20
3.5 Face Candidates Confirmation Using Fuzzy Logic Inference . . 22
3.5.1 Fuzzy Logic Introduction . . . . . . . . . . . . . . . . . 22
3.5.2 Face Candidates Confirmation . . . . . . . . . . . . . . 23
4 Experimental Results 28
4.1 System Requirement . . . . . . . . . . . . . . . . . . . . . . . 28
4.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . 29
4.2.1 Simulation Data Set . . . . . . . . . . . . . . . . . . . 29
4.2.2 Skin Region Extraction . . . . . . . . . . . . . . . . . . 30
4.2.3 Eye Detection . . . . . . . . . . . . . . . . . . . . . . . 31
4.2.4 Face Detection . . . . . . . . . . . . . . . . . . . . . . 33
5 Conclusion and Future Works 51
5.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

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