Abstract The average ridge distance of a fingerprint image is an important characteristic of fingerprint texture attribute. As an important parameter, the precision of estimation seriously affects the results of segmentation, enhancement and classification of fingerprint recognition. An algorithm is proposed to compute the average ridge distance of fingerprint accurately by using discrete Fourier transform, discrete information entropy theory, and weighted Euclidean distance. To evaluate the performance of the proposed algorithm, an experimental scheme is put forward based on man-made experimental datasets and typical fingerprint images. The experimental results show that the proposed algorithm estimates the average ridge distance accurately.
[1] Maltoni D, Maio D, Jain A K, et al. Handbook of Fingerprint Recognition. New York, USA: Springer-Verlag, 2003 [2] Bazen A M, Gerez S H. Segmentation of Fingerprint Images // Proc of the 12th Annual Workshop on Circuits, Systems and Signal Processing. Veldhoven, Netherlands, 2001: 276-280 [3] Jain A J, Flynn P, Ross A A. Handbook of Biometrics. New York, USA: Springer-Verlag, 2007 [4] Hong Lin, Jain A K, Pankati S, et al. Fingerprint Enhancement // Proc of the IEEE Workshop on Applications of Computer Vision. Sarasota, USA, 1996: 202-207 [5] Zhu En, Yin Jianping, Zhang Guomin, et al. A Gabor Filter Based Fingerprint Enhancement Scheme Using Average Frequency. International Journal of Pattern Recognition and Artificial Intelligence, 2006, 20(3): 417-430 [6] Maio D, Maltoni D. Ridge-Line Density Estimation in Digital Images // Proc of the 14th International Conference on Pattern Recognition. Brisbane. Australia, 1998, Ⅰ: 534-538 [7] Zhu En, Yin Jianpin, Zhou Jing. Fingerprint Classification by Using Average Period. Journal of National University of Defense Technology, 2004, 26(4): 22-26 (in Chinese) (祝 恩,殷建平,周 婧.使用平均周期进行指纹分类.国防科技大学学报, 2004, 26(4): 22-26) [8] Kovacs-Vajna Z M, Rovatti R, Frazzoni M. Fingerprint Ridge Distance Computation Methodologies. Pattern Recognition, 2000, 33(1): 69-80 [9] O’Gorman L, Nickerson J V. An Approach to Fingerprint Filter Design. Pattern Recognition, 1989, 22(1): 29-38 [10] Hung D C D. Enhancement and Feature Purification of Fingerprint Images. Pattern Recognition, 1993, 26(11): 1661-1671 [11] Yin Yilong, Tian Jie, Yang Xiukun. Ridge Distance Estimation in Fingerprint Images: Algorithm and Performance Evaluation. EURASIP Journal on Applied Signal Processing, 2004, 4: 495-502 [12] Zhu En, Yin Jianpin, Zhang Guomin. Computation of Fingerprint Inter-Ridge Distance. Microelectronics & Computer, 2004, 21(10): 7-9 (in Chinese) (祝 恩,殷建平,张国敏.指纹纹路间距的计算.微电子学与计算机, 2004, 21(10): 7-9) [13] Zhan Xiaosi, Sun Zhaoai, Yin Yilong, et al. Fingerprint Ridge Distance Estimation: Algorithms and the Performance // Proc of IAPR International Conference on Biometrics. Hongkong, China, 2006: 294-301 [14] Zuo Junyi, Zhao Chunhui, Pan Quan, et al. A Novel Binary Image Filtering Algorithm Based on Information Entropy // Proc of the 6th World Congress on Intelligent Control and Automation. Dalian, China, 2006, Ⅱ: 10375-10379 [15] Gower J C, Legendre P. Metric and Euclidean Properties of Dissimilarities Coefficients. Journal of Classification, 1986, 3(1): 5-48 [16] Maio D, Maltoni D, Cappelli R, et al. FVC2000: Fingerprint Verification Competition. IEEE Trans on Pattern Analysis and Machine Intelligence, 2002, 24(3): 402-412
2009, Vol. 22 
