tailieunhanh - Báo cáo hóa học: " Ridge Distance Estimation in Fingerprint Images: Algorithm and Performance Evaluation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Ridge Distance Estimation in Fingerprint Images: Algorithm and Performance Evaluation | EURASIP Journal on Applied Signal Processing 2004 4 495-502 2004 Hindawi Publishing Corporation Ridge Distance Estimation in Fingerprint Images Algorithm and Performance Evaluation Yilong Yin College of Computer Science Technology Shandong University Shanda South Road 27 Jinan 250100 China Email ylyin@ Jie Tian Intelligent Bioinformatics Systems Division Institute of Automation The Chinese Academy of Sciences Beijing 100080 China Email tian@ Xiukun Yang Identix Inc One Exchange Place Suite 800 Jersey City NJ 07302 USA Email Received 17 October 2002 Revised 27 September 2003 It is important to estimate the ridge distance accurately an intrinsic texture property of a fingerprint image. Up to now only several articles have touched directly upon ridge distance estimation. Little has been published providing detailed evaluation of methods for ridge distance estimation in particular the traditional spectral analysis method applied in the frequency field. In this paper a novel method on nonoverlap blocks called the statistical method is presented to estimate the ridge distance. Direct estimation ratio DER and estimation accuracy EA are defined and used as parameters along with time consumption TC to evaluate performance of these two methods for ridge distance estimation. Based on comparison of performances of these two methods a third hybrid method is developed to combine the merits of both methods. Experimental results indicate that DER is and EA is 84 93 and 91 and TC is and seconds with the spectral analysis method statistical method and hybrid method respectively. Keywords and phrases fingerprint ridge distance spectral analysis statistical window hybrid method. 1. INTRODUCTION Fingerprint identification is the most popular biometric technology and has drawn a substantial attention recently 1 . An automated fingerprint identification system AFIS includes fingerprint acquisition feature extraction