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研究生:蔡孟傑
研究生(外文):Meng-Chieh Tsai
論文名稱:高效能非正向視角虹膜辨識系統
論文名稱(外文):A High Performance Non-orthogonal View Iris Recognition System
指導教授:石勝文石勝文引用關係
指導教授(外文):Sheng-Wen Shih
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:資訊工程學系
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:2007
畢業學年度:95
語文別:中文
論文頁數:59
中文關鍵詞:生物特徵虹膜辨識非正向視角仿射轉換
外文關鍵詞:biometricsiris recognitionnon-orthogonal biometricsiris recognitionnon-orthogonal viewaffine rectification
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近年來,由於傳統身份辨識方法的諸多問題,使得利用個人生物特徵來辨識身份的技術
逐漸受到重視。由於虹膜辨識技術有良好的便利性與辨識率,使其在眾多的生物辨識技
術當中脫穎而出,廣為使用。傳統的虹膜辨識系統均是假設使用者在正視攝影機的情況
下擷取虹膜影像,然而此項假設會限制住虹膜辨識的應用範圍。本論文將深入探討使用
在非正向的情形下所攝得之虹膜來辨識個人身份的技術。本研究的目標有二:一為利用
即有的硬體架構取得不同視角的近紅外光與可見光彩色的四頻譜虹膜影像,並且改良舊
有系統中虹膜影像品質評估的方法,對虹膜定位與特徵比對的部份做最佳化,使得系統
能夠快速的進行辨識,並且依舊擁有良好的辨識率。二為驗証仿射矯正 (Affine
Rectification) 是否適用於將非正向的虹膜影像轉換為正向視角的虹膜影像。實驗結
果顯示,改進後的系統不但有較高的效率,也具有較好的辨識效果。
In recent years, techniques for personal identification with biometrics have
drawn more and more attention from people due to the insecurity of the
traditional authentication methods. Because of the convenience and high
recognition accuracy, iris recognition techniques have stood out among the
biometric personal identification techniques and are widely adopted in many
applications. Most of the existing iris recognition systems are developed
under the assumption that the iris images are acquired with the orthogonal
view imaging condition (OVIC). This assumption has restricted the
applicability of iris recognition systems. In this thesis, we will discuss
in depth an iris recognition technique that considers the non-orthogonal
view iris image for personal identification. The purpose of this study is
twofold. The first is to improve the iris image quality assessment method
and to optimize the iris localization and classification process of our
pervious four-spectral iris recognition system. The second is to verify
whether the affine rectification is appropriate to convert a non-orthogonal
view iris image into an orthogonal view image. Experiments show that the
improved system has higher efficiency and better recognition accuracy.
1 簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1 動機與目的. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 文獻探討. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 系統流程. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 研究成果. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 章節架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 虹膜取像硬體架構8
2.1 硬體架構簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2 雙CCD 取像模組. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3 雙CCD 攝影機影像校正. . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3 虹膜影像品質評估. . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1 瞳孔定位. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.2 清晰度測量. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.3 動態模糊偵測. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4 虹膜定位與特徵萃取21
4.1 仿射矯正. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2 虹膜定位. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.3 眼瞼定位. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.4 虹膜影像正規化. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.5 特徵萃取. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.6 虹膜碼比對. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5 仿射矯正影像分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1 虹膜特徵成像模擬. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1.1 簡化眼球光學膜型. . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1.2 無失真攝影機模型. . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.1.3 虹膜特徵在不同角度間成像位移分析. . . . . . . . . . . . . . . . . 36
5.2 真實虹膜影像特徵位移量之計算. . . . . . . . . . . . . . . . . . . . . . . . 37
6 實驗結果. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
6.1 虹膜定位. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
6.2 系統速度. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
6.2.1 影像品質評估. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
6.2.2 特徵萃取. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.2.3 分類. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.2.4 總結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6.3 仿射矯正影像分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
7 結論與未來展望. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
7.1 結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
7.2 未來展望. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
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