臺灣博碩士論文加值系統

本論文提出一套智慧型電腦使用者眼睛保護系統，適用於複雜背景以及受測者戴眼鏡的情況。經由視訊攝影機，擷取電腦使用者以及週遭工作環境的影像，應用人臉辨識的技術，進行使用者身分辨別，並且利用人臉資訊進行視距偵測及眨眼判斷。若電腦使用者常常沒有保持適當的視距、每分鐘的眨眼數太少或太多、長時間使用電腦及環境光源太亮或不足時，系統會使用圖片、文字和聲音來給予電腦使用者適當的警告，達到主動保護眼睛的目的。
在本論文中應用的技術包括人臉偵測、人臉辨識、視距偵測及眨眼偵測等。在人臉偵測的部分，將CCD視訊攝影機所擷取的彩色影像作為系統輸入，消除環境光源對彩色影像的影響後，進行灰階處理、二值化與連通域標記演算法及型態學等方法的處理，找出影像中的膚色區域，並在每個膚色區域中確認是否為人臉，完成影像中的人臉偵測。在人臉辨識的部分，將人臉影像經由主成分分析(PCA)法做轉換，再將待辨識人臉影像以歐氏距離(Euclidean distance)來判定是否為不同的使用者。在視距偵測部分，藉由橢圓形搜尋法，來獲得臉部寬度資訊，藉此來偵測視距。眨眼偵測部分，在人臉中進行動差運算，經由眼睛範圍內白色點數變化量的統計，快速地偵測使用者是否眨眼，以每分鐘眨眼次數來評估使用者的眼睛疲勞程度。

In this study, we developed a wisdom system that can actively remind the computer user to let his/her eyes take a break. This system uses a PC camera to capture the image of the user and the background. It applies recognition technology to validate the user. At the same time, the system uses a built-in timer to record how long the user has worked on the computer. When the user is using the computer, the system not only detects the visual distance but also count the eye’s blinks by the facial feature.

If the user doesn’t keep a proper visual distance from the monitor of the computer, his/her eyes’ blinks too often or too less, his/her has used the computer for a long time, illumination is too bright or too dark according to the background lighting behind the user, or the user uses computer not within a proper time, the system will pop up a warning message via words /voice to inform the user. Therefore, this system can initiatively be used to protect computer user’s eyes from harm.

This system consists of three parts: the face detection, the face recognition, the visual distance detection and the blink detection technology.

In the face detection part, a PC camera is used to capture the color image, and then the environment noise is removed by doing connected component labeling and morphology process to find human face. In the face recognition part, we use Principal Component Analysis technology to extract the feature of human face, and then use Euclidean distance technology to validate the user. In the visual distance detection part, Ellipse mask method is used for obtaining face information and detecting user visual distance from the monitor of computer. In the blink detection part, set the eyes region to count the blinks frequency to estimate the user weary degree.

摘要 ……………………………………………………………………I
ABSTRACT ………………………………………………………………II
致謝 ……………………………………………………………………IV
目錄 ……………………………………………………………………V
圖目錄 …………………………………………………………………X
表目錄 …………………………………………………………………XV
第一章 緒論 ……………………………………………………………1
1.1 研究動機 ………………………………………………………1
1.2 研究目標 ………………………………………………………1
1.3 系統架構 ………………………………………………………2
1.4 論文架構 ………………………………………………………4
第二章 人臉偵測 ………………………………………………………5
2.1 人臉偵測導論 …………………………………………………5
2.1.1 人臉偵測問題 ……………………………………………5
2.1.2 顏色分割 …………………………………………………6
2.1.3 人臉偵測方法 ……………………………………………7
2.2 人臉偵測系統流程 ……………………………………………9
2.3 膚色檢測 ………………………………………………………12
2.3.1 膚色範圍偵測 ……………………………………………12
2.3.2 雜訊去除 …………………………………………………16
2.3.3 膚色區域判定 ……………………………………………17
2.4 橢圓頭部比對 …………………………………………………19
2.4.1 影像濾波 …………………………………………………19
2.4.2 邊緣偵測 …………………………………………………20
2.4.3 人臉遮罩偵測 ……………………………………………22
2.5 嘴唇特徵偵測 …………………………………………………25
2.5.1 嘴唇搜尋空間 ……………………………………………25
2.5.2 嘴唇唇色偵測 ……………………………………………26
2.6 視距偵測 ………………………………………………………27
2.6.1 視距偵測方法 ……………………………………………27
2.6.2 視距偵測校正 ……………………………………………30
第三章 眨眼偵測 ……………………………………………………32
3.1 眨眼偵測導論 …………………………………………………32
3.1.1 眨眼偵測問題 ……………………………………………32
3.1.2 眨眼偵測方法 ……………………………………………33
3.2 眨眼偵測系統流程 ……………………………………………37
3.3 眼睛特徵偵測 …………………………………………………38
3.3.1 眼睛搜尋空間 ……………………………………………38
3.3.2 眼睛定位 …………………………………………………39
3.4 眨眼偵測演算法 ………………………………………………42
3.4.1 眨眼偵測空間 ……………………………………………42
3.4.2 點數變化 …………………………………………………44
3.4.3 眨眼深度門檻值 …………………………………………45
第四章 人臉辨識 ……………………………………………………48
4.1 人臉辨識導論 …………………………………………………48
4.1.1 人臉辨識問題 ……………………………………………48
4.1.2 人臉辨識方法 ……………………………………………49
4.2 人臉辨識系統流程 ……………………………………………52
4.3 臉部影像前置處理 ……………………………………………54
4.3.1 亮度補償 …………………………………………………54
4.3.2 影像正規化 ………………………………………………55
4.4 PCA用於人臉辨識 ……………………………………………56
4.4.1 PCA 原理介紹 ……………………………………………56
4.5 歐氏距離決策法 ………………………………………………60
4.6 人臉資料庫建構 ………………………………………………61
第五章 實驗結果與討論 ……………………………………………63
5.1 實驗環境軟硬體設施 …………………………………………63
5.1.1 硬體特性需求 ……………………………………………64
5.1.2 Windows SDK函式庫 ……………………………………65
5.2 系統操作介面介紹 ……………………………………………67
5.3 系統功能總覽 …………………………………………………69
5.4 人臉偵測系統測試 ……………………………………………70
5.4.1 人臉偵測結果 ……………………………………………70
5.4.1.1 頭部旋轉角度偵測 …………………………………71
5.4.1.2 不同光線照明偵測 …………………………………72
5.4.1.3 複雜背景下偵測 ……………………………………74
5.4.1.4 GTAV 資料庫測試 …………………………………75
5.4.2 視距偵測 …………………………………………………78
5.5 眨眼偵測系統測試 …………………………………………79
5.5.1 眼睛偵測 ………………………………………………80
5.5.1.1 頭部旋轉角度偵測 ………………………………80
5.5.1.2 不同光線照明偵測 ………………………………81
5.5.1.3 複雜背景下偵測 …………………………………83
5.5.1.4 GTAV 資料庫測試 …………………………………85
5.5.2 眨眼頻率偵測 …………………………………………88
5.5.3 疲勞偵測 …………………………………………………91
5.6 人臉辨識系統測試 ……………………………………………92
5.6.1 使用者身分辨識 …………………………………………93
5.6.2 使用者使用時間管理 ……………………………………96
5.6.3 使用者登入登出紀錄 ……………………………………98
第六章 結論與未來研究方向 ………………………………………99
6.1 結論 …………………………………………………………99
6.2 未來研究方向 ………………………………………………101
附錄一 色彩空間 ……………………………………………………102
附錄二 形態學 ………………………………………………………106
參考文獻 ……………………………………………………………119

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