指紋是個人獨一無二的特徵，而且已經被用來做個人辨識許多年了，然而一個理想的自動指紋辨識系統始終不存在。這一篇指紋利用兩大類來進行自動指紋辯識：指紋分類與特徵比對，指紋分類可以減少特徵比對的時間。指紋主要分為五大類：”Arch”、”Left Loop”、”Right Loop”、”Whorl”和”Others”，然後有兩個特徵”Endings”和”Bifurcations”必須被偵測出來，來進行比對。

我們的辨識系統測試了6個資料庫，分別從我們實驗室收集出來的Right28和Lindex101的兩個資料庫，和FVC2000所提供的DB1、DB2、DB3和DB4的四個資料庫。這個實驗是在Athelon XP 2500 CPU和512 MB SDRAM的電腦上，在Windows XP的作業系統上所進行的。每次比對大至花了0.2秒的時間。我們實驗出來的辨識率分別是Right28：98.21% (110/112)、Lindex101：87.87% (355/404)、DB1：95.00% (76/80)、DB2：93.75% (75/80)、DB3：88.75% (71/80)和DB4：81.25% (65/80)。大部分辨識失敗的主要原因是一些無法避免的雜訊。

Fingerprints of a personal unique characteristic have been used as an individual identification for many years. However, a perfect automatic fingerprint identification system (AFIS) does not exist. This thesis implements an AFIS with the use of fingerprint classification and minutiae pattern matching. The former stage may reduce the time of process for the latter stage. The fingerprint can be classified into five categories: arch, left loop, right loop, whorl, and others. Then minutiae, ridge endings and bifurcations, are detected for matching.

Our system is tested on 6 databases of fingerprints, such as Right28 , Lindex101 from PRIP Lab at NTHU and DB1, DB2, DB3, DB4 provided by FVC2000, on a PC with Athelon XP 2500 CPU and 512 MB SDRAM running Windows XP OS. Each match takes around 0.2 seconds. Among the first 3 best ranks, we achieve 98.21% (110/112), 87.87% (355/404), 95% (76/80), 93.75% (75/80), 88.75% (71/80), and 81.25 (63/80) respectively in these 6 databases. Most of non-matched images are due to unavoidable noise.

[Baz00] A.M. Bazen, and S.H. Gerez, “Directional Field Computation for Fingerprints Based on the Principal Component Analysis of Local Gradients”, In Proc. ProRISC2000 Workshop on Circuits, Systems and Signal Processing, Veldhoven, The Netherlands, November 2000.

[Baz01] A.M. Bazen and S.H. Gerez, “Segmentation of Fingerprint Images”, In Proc. ProRISC2001 Workshop on Circuits, Systems and Signal Processing, Veldhoven, The Netherlands, November 2001.

[Cha03] C.Y. Chang, “Automatic Fingerprint Verification System”, M.S. Thesis, National Tsing Hua University, June 2003.

[Che02] Y.Y. Chen, “Fingerprint Image Classification Based on Singular Points”, M.S. Thesis, National Tsing Hua University, June 2002.

[Con02] V. Conti, G. Pilato, S. Vitabile, F. Sorbello, “Verification of Ink-on-paper Fingerprints by Using Image Processing Techniques and a New Matching Operator”, VIII Convegno AI*IA, Siena 10-13, 594-601, Sept. 2002.

[Esp02] V. Espinosa-Duro, “Minutiae detection algorithm for fingerprint recognition”, IEEE Aerospace and Electronics Systems Magazine, Vol. 17, No. 3, 7-10, 2002.

[Gon92] R.C. Gonzalez and R.E. Woods, “Digital Image Processing”, Reading, MA: Addison-Wesley Publishing Company, 3rd Edition, 1992.

[Hon98] L. Hong, Y. Wan, and A. Jain, “Fingerprint Image Enhancement: Algorithm and Performance Evaluation”, IEEE Transactions on Pattern Analysis Machine Intelligence, Vol. 20, No. 8, 777-789, 1998.

[Kar96] K. Karu, and A.K. Jain, “Fingerprint Classification”, Pattern Recognition, Vol. 29, No. 3, 284-404, 1996.

[Ko02] T. Ko, “Fingerprint enhancement by spectral analysis techniques”, The Proceedings of Applies Imagery Pattern Recognition Workshop, 133-139, 2002.

[Luo00] X. Luo, J. Tian and Y. Wu, “A Minutia Matching algorithm in Fingerprint Verification”, 15th ICPR, Vol.4, 833-836, 2000

[Mai02] D. Maio, D. maltoni, R. Cappelli, J.L. Wayman, and A.K. Jain, “FVC2000: Fingerprint Verification Competition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 3, 2002.

[Nac84] N.J. Naccache and P. Shinghal, “An Investigation into the Skeletonization Approach of Hilditch”, Pattern Recognition, Vol. 17, No. 3, 279-284, 1984.

[Rat96] N. K. Ratha, K. Karu, S. Chen, and A. K. Jain, “A Real-Time Matching System for Large Fingerprint Databases”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, 1996.

[Sen01] A.Senior, “A Combination Fingerprint Classifier”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 10, 2001

[Wan01] Y. I. Wang, “An AFIS Using Fingerprint Classification”, M.S. Thesis, National Tsing Hua University, June 2001.

[Zor01] D. S. Zorita, J.O. Garcia, S. C. Lianas, and J. G. Rodriguez, “Minutiae extraction scheme for fingerprint recognition systems”, International Conference on Image Processing, Vol. 2, 254-257, 2001.