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研究生:王聖文
研究生(外文):Sheng-Wen Wang
論文名稱:自動眼睛偵測及眼鏡去除方法
論文名稱(外文):Automatic Eye Detection and Glasses Removal
指導教授:張志永
指導教授(外文):Jyh-Yeong Chang
學位類別:碩士
校院名稱:國立交通大學
系所名稱:電機與控制工程系所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:66
中文關鍵詞:眼睛偵測眼鏡移除臉部輪廓擷取環狀頻率濾波器膚色圖
外文關鍵詞:Eye detectionGlasses removalFace segmentationCircle-frequency filterSkin-color map
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在本篇論文中,我們提出一演算法,使其能夠在一張人臉影像中偵測眼睛的位置,並且在該人臉有戴眼鏡時,去除眼鏡的干擾。此系統包含三個模組:臉部位置偵測,眼睛偵測,以及當受測者有戴眼鏡時,去除眼鏡的方法。首先,我們使用通用膚色圖偵測臉部區域,以確保在周遭光源條件變化時,仍有足夠的適應性。接著,採用在臉部傾向及旋轉上有良好不變性的環狀頻率濾波器,偵測眼睛區域。最後,由於眼鏡的普遍使用,提出以邊緣偵測及改良的模糊規則型式的濾波器,預測眼鏡區域的像素值。結果顯示,我們提出的方法在眼睛偵測是有效率的,並且在眼鏡去除上也能得到良好的品質。
This thesis addresses an algorithm to automatically detect the eye location from a given face image and remove the glasses while one has worn. Our system consists of three modules: face segmentation, eye detection, and eyeglasses removal while one has worn on eyeglasses. First, we use the universal skin-color map to detect the face regions, which can ensure sufficient adaptability to ambient lighting conditions. Then, a special filter, called circle-frequency filter, is used to locate the eye regions because of its invariant characteristic in wide face orientations and rotations. Finally, for the widely using of glasses, we proposed a novel method to remove the eyeglasses automatically based on edge detection and modified fuzzy rule-based (MFRB) filter. The simulation and results demonstrate that our approach detects eye location efficiently and demonstrates high fidelity to the non-wearing-glasses facial image after glasses removal.
摘要 ………………………………….……………………………………………… i
ABSTRACT ………………………………………………………………………… ii
ACKNOWLEDGEMENT ………………………………………………………… iii
CONTENTS ………………………………………………………………….…….. iv
LIST of FIGURES ………………………………………………………….……… vi
LIST of TABLES …………………………………………………………………. viii

CHAPTER 1 INTRODUCTION ………………………………………………... 1
1.1 Motivation of This Research ……………………………………………........ 1
1.2 Face Detection ……………………………………………………………….. 2
1.3 Eye Location ……………………………………………………………….... 4
1.4 Glasses Existence Detection and Glasses Removal …………………………. 5
1.5 Flowchart of Eye Detection and Glasses Removal System …………….…… 6
1.6 Thesis Outline …………………………………………………..…………… 7

CHAPTER 2 FACE SEGMENTATION ………………………………………. 10
2.1 Introduction ………………………………………………………………… 10
2.2 Color Analysis ……………………………………………………………… 11
2.3 Face Segmentation Algorithm ……………………………………………… 13

CHAPTER 3 EYE DETECTION and GLASSES REMOVAL ..….………….. 23
3.1 Introduction to Eye Detection ….………………………………………....... 23
3.2 Circle-Frequency Filter …………………………………………………….. 24
3.3 “Between-Eyes” Candidate Evaluation …………………………………..… 26
3.4 Tracking “Between-Eyes” ………………………………………………….. 27
3.5 Glasses Existence Detection ……………………………………………...… 28
3.6 Eye Location While Wearing Glasses …………………………………….... 29
3.7 Glasses Removal ………………………………………………………….... 30

CHAPTER 4 SIMULATION and RESULTS ……………………………….… 39
4.1 Non-Wearing Glasses Cases ……………………………………………...… 39
4.2 Wearing Glasses Cases ……………………………………………………... 44

CHAPTER 5 CONCLUSION ………………………………………………….. 52

REFERENCES ………………………………………………………………….… 54
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[13] R. Thilak Kumar, S. Kumar Raja, and A. G. Ramakrishnan, “Eye detection using color cues and projection functions,” in Proc. IEEE Int. Conf. Image Processing, 2002, vol. 3, pp. 24–28.

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[18] C. Wu, C. Liu, H. Y. Shum, Y. Q. Xu, and Z. Zhang, “Automatic eyeglasses removal from face images,” in Proc. 5th Asia Conf. Computer Vision, 2002, pp. 23–25.

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