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研究生:張庭瑄
研究生(外文):Ting-Hsuan Chang
論文名稱:自動紅眼消除使用快速臉部偵測
論文名稱(外文):Automatic Red-Eye Reduction with Fast Face Detection
指導教授:傅楸善傅楸善引用關係
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:資訊工程學研究所
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:2008
畢業學年度:96
語文別:英文
論文頁數:50
中文關鍵詞:人臉偵測紅眼消除膚色偵測
外文關鍵詞:face detectionred-eye reductionskin-tone detection
相關次數:
  • 被引用被引用:0
  • 點閱點閱:200
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
紅眼消除的技術是為了減少照片中的不協調的地方。此種技術能讓使用者得到更好的照片列印成果。近年來數位相機與行動電話的普及,使得人們可以輕鬆的拍取大量的相片,其中不乏在暗處使用閃光燈所拍攝到含有紅眼現象的圖片,而如何消除這個影響,已經成為一個重要的課題。
在這篇論文裡面,我們提出使用快速臉部偵測與自動偵測紅眼並消除的方法,自動的將影像中紅眼的部位消除,同時增快處理速度與降低假警報出現的機率,呈現出一張更為完美的輸出照片。
Red-Eye Reduction Technology is used for some artifacts in still images. This technology can help user get a better photo print. In recent years, digital cameras and camera phones are more popular. People can take many pictures easily. Some photos taken in dark with flashlight will have some red-eye artifact. This subject becomes more important nowadays.
In this thesis, we propose a fast face detection and automatic red-eye reduction method, which eliminates red-eye effect automatically. Increasing the processing speed and decreasing the false alarm rate to produce a better photo print.
口試委員會審定書 i
誌 謝 ii
摘要 iii
Abstract iv
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Cause of Red Eye 2
Chapter 2 Related Work 4
2.1 Hardware solutions 4
2.2 Software Solutions 6
Chapter 3 Face Detection Method 13
3.1 Face Detection in Color Images 13
3.2 AdaBoost and Haar-like Filter 19
Chapter 4 Our Proposed Method 22
4.1 Accelerated Face Detection 22
4.2 Skin-Tone Verifying 26
4.3 Red-Eye Locating 27
4.4 Red-Eye Removal 30
Chapter 5 Experiment Results 33
5.1 Experiment environment 33
5.2 Experiment Result 34
5.3 Comparison 44
Chapter 6 Conclusion and Future Work 47
6.1 Conclusion 47
6.2 Future Work 47
Reference 49
[1] Biometric Watch, “Retinal Recognition,” http://www.biometricwatch.com/Technologies/Retina_recognition/retina.htm, 2005.
[2] CNRI.EDU, “Pupil Deformations,” http://cnri.edu/content.asp?contentid=522, 2007.
[3] G4 Media, Inc., “Photoshop Tip: Eliminate Red Eye,” http://www.g4tv.com/techtvvault/features/35394/Photoshop_Tip_Eliminate_Red_Eye.html?article_key=35394, 2008.
[4] M. Gaubatz and R. Ulichney, “Automatic Red Eye Detection and Correction,” Proceedings of IEEE International Conference on Image Processing, Rochester, New York, pp. 804-807, 2002.
[5] R. L. Hsu, M. Abdel-mottaleb, and A.K. Jain, “Face Detection in Color Images”, Proceedings of the International Conference on Image Processing, Thessaloniki, Greece, pp. 1046-1049, 2001.
[6] J. Y. Kasprzak, “Red Eye Reduction,” http://www.fi.muni.cz/~kas/blog/index.cgi/2006/04/index.html, 2006.
[7] Y. N. Lien, “Camera/VideoCam,” http://www.cs.nccu.edu.tw/~lien/BCC/IO/hardcopy.htm, 2003.
[8] H. T. Luo, J. Yen, and D. Tretter, “An Efficient Automatic Redeye Detection and Correction Algorithm,” Proceedings of the International Conference on Pattern Recognition, Cambridge, United Kingdom, pp. 883-886, 2004.
[9] Photoshopium.com, “Red Eye Reduction Tutorial,” http://photoshopium.com/photo-effects/33/red-eye-reduction-tutorial, 2007.
[10] The-Digital-Picture.com, “Canon Off Camera Shoe Cord 2 Review,” http://www.the-digital-picture.com/Reviews/Canon-Off-Camera-Shoe-Cord-2-Review.aspx, 2007.
[11] P. Viola and M. Jones,“Rapid Object Detection Using a Boosted Cascade of Simple Features,” Proceedings of International Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, Vol. 1, pp. 511-518, 2001.
[12] F. Volken, J. Terrier, and P. Vandewalle, “Automatic Red-Eye Removal Based on Sclera and Skin Tone Detection,” Proceedings of IS&T European Conference on Color in Graphics, Imaging and Vision, Leeds, United Kingdom, pp. 359-364, 2006.
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