應用於辨識系統之虹膜特徵碼產生硬體設計

A Hardware Design of Iris Code Generation for Recognition System

李韋忠(Wei-Chung Lee)

指導教授 ： 朱元三

國立中正大學/工學院/電機工程學系/碩士(2014年)

摘要

隨著網路安全愈來愈受到重視，以目前盛行的PIN(Personal Identification Number)辨識來說，常常因為疏忽遺失或是錯誤接受的情況造成損失，此外，近年來恐怖攻擊事件頻傳，個人身份辨識的正確性變得更加重要，因此，捨棄煩人密碼，確立身分的唯一性，回歸到以人體特徵做為辨識主體的「生物辨識系統」已成為一股新的趨勢。
而虹膜識別是生物辨識技術中最準確的辨識方法之一，但卻受限到硬體設備、成本以及系統資源。因此本論文使用中國科學院自動化研究所提供的CASIA虹膜影像資料庫做為樣本，利用影像處理的技巧，使用虹膜特徵最明顯且最不受干擾的區塊，做虹膜的辨識，而虹膜樣本之辨識成功率達96.5%。此外，針對大多數的虹膜識別算法都是基於對中央處理單元（CPU）上運行的順序操作來實現，而本論文提出對虹膜辨識系統當中時間耗損最多的區塊，實現於積體電路上，並達到快速、有效的虹膜辨識及身分確認。

關鍵字

虹膜

並列摘要

With the network safety becomes more attention, the PIN (Personal Identification Number) recognition usually losses because the negligence or error to accept. In addition, there are several terrorist attacks in the recent years, so that the personal identification recognition becomes more important. Therefore , discarding the annoying password and establishing the uniqueness of identity, return to the “biometric identification system” which based on the human characteristics have been a new trend.
The iris recognition technology is one of the biometric identification methods which is the most accurate, but it is limited to the hardware, cost and system resources. In our thesis, we try to apply some methods of image processing to the database, which is provided by CASIA. We use the most undisturbed block of iris in the image which have the most obviously of iris features to do our recognition. The matching rate of the CASIA database could be 96.5%. However, most of iris recognition algorithms are implemented based on sequential operations running on central processing units (CPUs). As result, in our thesis we propose a fast and efficient design for iris recognition and implemented in integration circuit in order to improve the iris recognition performance.

並列關鍵字

Iris

參考文獻

[1] L. Flom and A. Safir, “Iris recognition system,” U.S.Patent, no.4641349,1987.

[2] John G. Daugman, “High confidence visual recognition of persons by a test of statical independence,” IEEE Trans.Patt.Anal. and Machine Intell., vol.15, no.11, pp.1148~1161,1993.

[3] John G. Daugman, “High confidence recognition of persons by iris patterns, ” IEEE 35th International Carnahan conference on Security Technology,254~263,2001.

[4] John G. Daugman," How Iris Recognition Works", IEEE Trans. on Circuits &

[5] R.P. Wildes, "Iris recognition: an emerging biometric technology", Proceedings of the IEEE, Vol. 85, No. 9, pp. 1348-1363,September 1997.