利用生物計量的方法來進行個人身份辨識目前越來越被廣泛討論。在眾多的生物計量方法中，又以指紋的特徵最常使用。在本篇論文中，我們建構一個指紋辨識系統。此系統是以一張由Veridicom FPS110 指紋擷取器所取得的影像為輸入，對此影像進行影像強化、分割、及細化的處理，並從已細化的指紋影像中抽取紋路的端點和分叉點及它們的紋路流向為特徵，經由這些特徵對資料庫中其他指紋進行比對的工作。
我們的資料庫中包含308張指紋影像，分別由77個不同人的右手食指，短時間內在指紋擷取器上連續按四次所得。本系統在PentiumII 400安裝128MRAM的個人電腦上進行實驗，實驗數據顯示，此指紋辨識系統平均花費6.78秒處理影像且進行比對，在錯誤接受率為3.25%的情況下，可達到88%的辨識率。

Biometric techniques used for personal identification have recently raised an increasing interest. Among many biometrics, features of fingerprint images are most frequently used. In this thesis, we develop a fingerprint identification system. Our system first takes a 300 ´ 300 fingerprint image, scanned via a Veridicom FPS110 reader, as input, does image enhancement, segmentation, and thinning to get a thinned image. From which, we find a minutiae pattern consisting of endings and bifurcations with their corresponding flow directions to best match those from a database.
Our database contains 308 fingerprint images contributed by 77 persons, each contributes 4 times of his right index fingerprints in a few minutes. Experiments on a Pentium II 400 PC with 128MB SDRAM show that the implemented system spends 6.78 seconds for processing and matching a fingerprint image, and it attains about 88% recognition rate with 3.25% false acceptance rate.

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