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研究生: 黃泰銓
Huang, Tai-Chuan
論文名稱: 三維度立體空間紅外線軌跡擷取應用在電子白板之實現
Implementation of Three-Dimensional Space Infrared Trajectory Capturing and Its Application to Interactive Whiteboard
指導教授: 廖德祿
Liao, Teh-Lu
學位類別: 碩士
Master
系所名稱: 工學院 - 工程科學系
Department of Engineering Science
論文出版年: 2011
畢業學年度: 99
語文別: 英文
論文頁數: 54
中文關鍵詞: 電子白板透視演算法
外文關鍵詞: Interactive whiteboard, Perspective algorithm
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  • 隨著科技進步,電子白板的應用已經漸漸被大眾所接受,但由於其成本較高,導致無法真正普及化,又近年來影像技術因電腦效能的提升,使得運用愈來愈廣泛,本論文以影像處理為基礎,搭配網路攝影機與紅外線光源實作出電子白板。
    為了要能夠有效分辨出紅外光與可見光的不同,本論文使用可見光遮罩有效的濾除可見光,僅留下所需判斷的紅外光影像供演算法判別。剩餘的紅外光影像在處理過程中,系統運用膨脹-侵蝕以減少因雜訊而使訊號判別所產生的誤差。最後將訊號透過透視演算法轉換成滑鼠座標或者螢幕座標,而達到能夠控制滑鼠與多點控制的目的。由於對整張影像擷取紅外線光源訊號,會花費較長的時間,因此本文提出移動式遮罩與多重移動式遮罩來改善這個問題,實驗結果顯示無論是在控制滑鼠或者多點控制,都可以得到較佳的效果。

    As technology advances, application of interactive whiteboard has become more popular. However, due to high cost it is not commonly available. Image technology in recent years, due to the improvement of computer efficiency, is applied in wide variety of uses. This thesis is based on image processing, implements the interactive whiteboard by matching webcam and an infrared light source.
    In order to effectively distinguish between infrared and visible light, this thesis uses visible light filter which effectively filter visible light. It leaves only the infrared image to be treated through algorithmic recognition. Using remaining infrared image for image processing, the system uses dilation-erosion to reduce the error caused by noise. Finally, signals are converted to mouse or screen coordinates to achieve the purpose of controlling the mouse or multiple points of control. As the entire image captures the infrared light source signals, will take long periods of time, so this thesis use mobile-mask and multiple mobile-mask to rectify the problem. The experimental results show that both in control of the mouse or multipoint control, it can receive better results in implementing the interactive white board.

    摘要 I Abstract II 誌謝 IV List of Figures VIII List of Tables X CHAPTER 1 INTRODUCTION 1 1.1 Motivation 1 1.2 Thesis Organization 2 CHAPTER 2 FUNDAMENTAL KNOWLEDGE 3 2.1 Image Processing Technique 3 2.1.1 Color Model Conversion 3 2.1.1.1 RGB Color Space 3 2.1.1.2 CMY Color Space 4 2.1.1.3 HSI Color Space 4 2.1.1.4 YUV Color Space 5 2.1.2 Image Noise Filtering 6 2.1.2.1 Averaging Spatial Filtering 6 2.1.2.2 Sharpening Spatial Filtering 6 2.1.2.3 Median Spatial Filtering 7 2.1.2.4 Ideal Low-Pass Filter 7 2.1.2.5 Butterworth Low-Pass Filter 8 2.1.2.6 Gauss Low-Pass Filter 9 2.1.3 Image Intensification 9 2.1.3.1 Histogram Equalization 9 2.1.3.2 Histogram Statistics 10 2.1.3.3 Arithmetic/Logic Operations Increased 11 2.2 Object Motion Detection Algorithm 12 2.2.1 Background Subtraction 13 2.2.2 Adaptive Background Subtraction 13 2.2.3 Modified Adaptive Background Subtraction 15 2.2.4 Content-Based Segment 15 2.2.5 Optical Flow 16 2.3 Perspective 17 2.3.1 One-Point Perspective 18 2.3.2 Two-Point Perspective 18 2.3.3 Three-Point Perspective 18 CHAPTER 3 ARCHITECTURE AND DESIGN 19 3.1 System Architecture 19 3.2 Webcam 21 3.3 Invisible Light Image Processing 21 3.3.1 Derived Invisible Light 22 3.3.2 Noise Filtering 22 3.3.2.1 Dilation 23 3.3.2.2 Erosion 24 3.4 Mouse Path Detection 25 3.4.1 Location 25 3.4.2 Coordinate System Transformation 27 3.4.3 Accelerated of Point Detection 29 3.5 Multi-Touch Path Detection 31 3.5.1 Location 31 3.5.2 Coordinate System Transformation 32 3.5.3 Accelerated of Point Detection 33 CHAPTER 4 TESTING AND RESULTS 35 4.1 Experimental Devices 35 4.1.1 Webcam 35 4.1.2 Self-Made Infrared Light Source 36 4.2 Software Application 39 4.3 Single-Point Tracking Results 43 4.4 Multi-Point Tracking Results 47 CHAPTER 5 CONCLUSION 51 Reference 53

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