摘要： 将两枚指纹相似性的判断归为一个二分类问题，介绍了一种基于支持模型和SVM的指纹匹配方法，采用了基于支持模型的细节特征匹配求取匹配的特征点集合，并利用匹配细节特征点所包含的匹配信息，对训练样本构造匹配向量进行分类训练。将训练后的分类器应用于FVC2002的测试数据库，实验结果表明该方法优于传统的计算方法，在度量指纹相似性方面是有效而且可靠的，且具有较强的推广性。

关键词: 指纹识别, 点模式匹配, 支持模型, 支持向量机

Abstract: This paper introduces a fingerprint matching algorithm based on the support model and support vector machine where calculating the similarity is considered as a general classification problem. The algorithm establishes the minutiae correspondence between two fingerprint images based on the support model, and constructs the feature vectors of a SVM using the minutiae’s matching relationships. The similarity of these two fingerprints is then measured by the distance between the feature vector and the decision hyper-plane of the SVM. Experimental results prove the method is more efficient than traditional methods. And it is robust and has strong generalization ability.

Key words: Fingerprint recognition, Point pattern match, Support model, SVM