采用PCNN模板的二值指纹图像改进细化算法  

Improved binary fingerprint image thinning algorithm using template-based PCNNs

作　　者：李百良[1] 徐大诚[1] 

机构地区：[1]苏州大学电子信息学院,江苏苏州215006

出　　处：《计算机工程与应用》2010年第17期169-170,193,共3页Computer Engineering and Applications

基　　金：江苏省高校自然科学研究基金项目 No.Q2116611~~

摘　　要：针对传统PCNN细化图像时存在细化不彻底、纹线的断裂、产生很多毛刺等问题,给出了一种采用PCNN并发特点对二值指纹图像进行细化的改进算法。经过分析图像细化后留下的毛刺特征,提出了几种消除模板。采用该模板能消除指纹细化后的毛刺;也有效地解决了细化不彻底的问题。利用FVC2004标准指纹图像库仿真的结果表明,指纹图像细化彻底,且能有效地消除纹线断裂和毛刺的产生。应用于指纹图像识别系统,提高了指纹的识别率。There is much trouble in thinning algorithm based on traditional PCNN,such as not thinning to one pixel,breaking the connectivity of ridge,generating spikes and so on.In order to overcome these disadvantages,an improved binary fingerprint image thinning algorithm based on parallel capability of PCNN is proposed.By analyzing character of spikes,some templates are proposed.Using these templates,the spikes and breaks can effectively be eliminated.Also,this method can effectively solve the less thorough thinning problem.The algorithm tests on FVC2004 database.The results show that the method can effectively reduce breaks and spikes,and apply to the automatic fingerprint recognition system to improve accept rate.

关 键 词：脉冲耦合神经网络 指纹图像 细化算法 三角模板 方形模板 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]