虹膜辨識

Iris Recognition

林文添(Wen-Ten Lin)

指導教授 ： 陳淑媛

元智大學/資訊學院/資訊工程學系/碩士(2006年)

https://doi.org/10.6838/YZU.2006.00283

摘要

虹膜辨識為生物辨識技術的一種，生物辨識的應用層面非常廣泛，如身分識別、資料安全控管、機場安全檢驗等。生物辨識技術種類很多，大致可區分為生物特徵及行為特徵兩種，生物特徵有指紋、掌紋、臉型、虹膜等；行為特徵有聲音、簽名等。在各種生物辨識技術中，虹膜辨識包含有較多資訊，而且也有相當的唯一性，並且從出生一歲後即定型不再改變，是生物辨識方法中相當有用的生物特徵。
本論文採用CASIA虹膜資料庫為測試資料來源，其中包含80位受測者，108只不同眼睛，每只眼睛有三張影像作為測試，四張影像作為訓練用途。系統的流程為瞳孔定位、虹膜定位、虹膜特徵擷取、虹膜特徵處理、資料庫比對。在影像前處理中從原來的眼球影像中定位出瞳孔位置，接著以瞳孔位置定位虹膜位置，並將圓環狀的虹膜轉換為長條型的虹膜特徵影像；將虹膜特徵影像進行眼皮與亮點去除，接著將虹膜特徵影像送入資料庫中比對。實驗結果證實所提方法確實有效且可行。

關鍵字

虹膜定位、虹膜影像前處理、虹膜辨識、相關係數、虹膜資料庫

並列摘要

Iris recognition is a kind of biometrics technology. The application of biometric recognition is tremendous such as person verification/identification, personal information security, and airport security. The features adopted in biometric technology can be divided into two groups: biological characteristic and behavior characteristic. The former includes fingerprint, palm, face, iris, etc. The latter includes speech, signing, gesture, etc. Among all, the iris involves more information, uniqueness, and invariable then other biological characteristics. It is a useful biological characteristic in the biometrics recognition.
Our method consists of three phases: pupil and iris location, iris feature image extraction and iris matching. The CASIA iris database was used in this study to evaluate the performance of the proposed method. The database includes 108 iris classes, each including seven images. In this study, four images are reserved for training and three images for testing. The effectiveness and practicability of the proposed method have been demonstrated by various experimental results.

並列關鍵字

Iris location, Iris preprocessing, Iris recognition, Correlation, Iris database

參考文獻

[1]. John Daugman, “Face and gesture recognition: overview,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, pp. 675-676, 1997.

[2]. John Daugman and Cathryn Downing, “Epigenetic randomness, complexity and singularity of human iris patterns,” Proc. R. Soc. Lond. B, pp. 1737-1740 , 2001.

[3]. John Daugman, “High confidence recognition of persons by iris patterns,” IEEE, pp. 254-263, 2001.

[4]. John Daugman, “How iris recognition works,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 1, pp. 21-30, 2004.

[5]. Eric Sung, Xi-Lin Chen, Jie Zhu and Jie Yang, “Towards non-cooperative iris recognition systems,” International Conference on Control, Automation, Robotics And Vision, pp. 990-995, 2002.