关键词: 指纹图像质量, 自动评测, 特征向量, 支持向量机分类器

Abstract: Accurate minutiae extraction from fingerprint images is heavily dependent on the quality of the fingerprint image.In order to improve the performance of the system，it is necessary to measure the quality of the captured fingerprint images.This paper presents a novel method for fingerprint image quality.Five features are extracted from the fingerprint image to analyze the quality and the feature vector is defined as being formed from the five features.Then an SVM classifier，which can solve small-sample learning problems with good generalization，is trained to classify the fingerprint image.The fingerprint image is separated into one of the three classes，good-quality，medium-quality，or poor-quality.Experimental results on FVC2004 and the private database show that the proposed method is an effective and efficient scheme to measure the quality of the fingerprint image.

Key words: fingerprint image quality, automatic measure, feature vector, Support Vector Machine classifier