適用區域範圍之指紋辨識系統設計與實現

Design and Implementation of an Embedded Fingerprint Recognition System for a Regional Area

林士永(Shi-Yong Lin)

指導教授 ： 鍾鴻源

國立中央大學/資訊電機學院/電機工程學系/碩士(2006年)

摘要

隨著科技日新月異，使得安全性議題 (Security)愈益受重視。故本論文提出以ARM (Advanced RISC Machines) RISC(Reduced Instruction Set Computer) 32-bit微處理器為主體，配合指紋模組(Fingerprint module) 設計能應用於區域規模的嵌入式指紋辨識系統(Embedded Fingerprint Recognition System, EFRS)。
經使用此系統，系統管理者能使用指紋登載 (Enrollment)、單人辨識 (Verification)、多人辨識 (Identification)等基本功能對被辨識者進行身份辨識。此論文亦設計一公用程式 (Utility program)，此公用程式不僅能讀取此嵌入式指紋辨識系統內部狀態與記錄狀況，並且能使多個嵌入式指紋辨識系統一起運作，使之能適用於比實驗室規模更廣泛的區域性範圍。故使用本論文提出的嵌入式指紋辨識系統，能幫助系統管理者了解系統運作狀況進而掌控所監控區域範圍內使用者所發生的活動。

關鍵字

指紋辨識模組 ； 嵌入式系統 ； 指紋 ； ARM ； 公用程式

並列摘要

Due to the advent of the emerging science and technology, the theme of security is getting more and more important. Herein, we present an Embedded Fingerprint Recognition System (EFRS), which consists of a fingerprint module and an ARM that is a microprocessor with 32 bits acting on RISC. The device can be applied to an embedded fingerprint recognition system in a regional area.
By using the EFRS, an EFRS manager can operate the enrollment, the verification, and the identification functions to check the user’s identity. In this study, we also present a utility program, which can read the records and fingerprints saved in the flash of a fingerprint module. The utility program can also integrate with each EFRS to work together, which makes the system used for a region area that is bigger than a laboratory. By analyzing the collected records, the EFRS manager can monitor the states of the EFRS and the activities users made.

並列關鍵字

utility program ； Fingerprint module ； ARM ； Fingerprint ； Embedded Fingerprint Recognition System

參考文獻

[2] S. G. Davies, Touching Big Brother, “How Biometric Technology Will Fuse Flesh and Machine,” Information Technology & People, Vol. 7, No. 4, pp. 60-69, 1994.

[6] Jeng Horng Chang, Kuo Chin Fan, “Fingerprint Classification by Ridge Distribution Sequence and Ridge Distribution Model,” Ph.D. thesis, National Central University, 2001.

[7] Wison Technology Corporation, “Fingerprint Module DSPspec,” Wison Technology Corporation, Taiwan, 2004.

[10] D. G. Joshi, Y. V. Rao, S. Kar, Valli Kumar and R. Kumar, “Computer-vision-based approach to personal identification using finger crease pattern, ” Pattern Recognition, Vol. 31, pp 15-22, 1998.

[12] Raffaele Cappelli, Alessandra Lumini, Dario Maio, Member, IEEE, and Davide Maltoni, “Fingerprint Classification by Directional Image Partitioning,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, No. 5, 1999.