基于神经网络的指纹识别

W. Leung, S. Leung, W. H. Lau, A. Luk
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引用次数: 69

摘要

作者描述了一种基于神经网络的自动指纹识别方法。采用带有一个隐藏层的多层感知器(MLP)分类器从指纹图像中提取细节。采用反向传播学习技术对其进行训练。选择的特征以一种特殊的方式表示,使它们在移动、旋转和缩放下同时保持不变。仿真结果表明,该方法具有较好的检测率和较低的故障率。结果表明,该方法对于具有少量指纹数据集的系统是可靠的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fingerprint recognition using neural network
The authors describe a neural network based approach for automated fingerprint recognition. Minutiae are extracted from the fingerprint image via a multilayer perceptron (MLP) classifier with one hidden layer. The backpropagation learning technique is used for its training. Selected features are represented in a special way such that they are simultaneously invariant under shift, rotation and scaling. Simulation results are obtained with good detection ratio and low failure rate. The proposed method is found to be reliable for a system with a small set of fingerprint data.<>
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