生物辨識可以根據每一個人生理上或行為上的特徵來準確的辨識身分，一般常見生理上的特徵有指紋、人臉與虹膜等等。在各種常見的生物辨識系統中，指紋辨識系統被認為是最常見且也是辨識度最高的系統。在最近幾年，指紋辨識系統被大規模的使用在各種不同的情況下，像是出入境管理、犯罪防治、刑事辨識等等用途中。
在本篇論文中，我們實作了一個基於特徵點比對的自動指紋辨識系統，我們的自動指紋辨識系統測試了2個資料庫，分別是從國立清華大學的圖形識別及影像處理實驗室所收集出來的Rindex28和Lindex101的兩個資料庫。這個實驗結果是在Intel Core i5 3.10GHz CPU和8 GB SDRAM的電腦上且在作業系統為Windows 7的環境底下執行,我們所實驗出來的辨識率分別是Rindex28：99.11% (111/112)、Lindex101：87.87% (355/404)。

Biometrics could accurately identify or verify individuals based upon each person’s unique physical or behavioral characteristics. Among all the biometric traits, fingerprint-based identification is the oldest method which has been successfully used in numerous applications. In recent years, automated fingerprint identification systems (AFIS) have been widely used, such as homeland security, law enforcement, criminal identification.
In this thesis, we implement a minutiae-based AFIS, our system tests on 2 databases of fingerprint images, such as Rindex28, Lindex101 from PRIP Lab at NTHU. The system environment is implemented on a system of Intel Core i5 with 3.10 GHz CPU and 8 GB SDRAM running Windows 7. According to the type of top 3 matches, the recognition rates are 99.11% (111/112), 87.87% (355/404), respectively.

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