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首页> 外文期刊>Journal of Imaging Science and Technology >Fingerprint Quality Assessment based on Texture and Geometric Features
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Fingerprint Quality Assessment based on Texture and Geometric Features

机译：基于纹理和几何特征的指纹质量评估

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摘要

Fingerprint quality assessments are generally used to evaluate the quality of images obtained from fingerprint sensors, and effective fingerprint quality assessment methods are crucial to establishing high-performance biometric identification systems. The use of fingerprint quality assessments helps improve the accuracy of fingerprint registration and user satisfaction. NIST Fingerprint Image Quality (NFIQ) is a popular fingerprint quality assessment algorithm; however, it is unable to provide high-quality assessments for some partial fingerprint images obtained from mobile device sensors. In this study, a hybrid fingerprint assessment framework that integrated texture and geometric features was examined. The final quality assessment values obtained by the framework were higher than those obtained using NFIQ, effectively elevating the performance of existing NFIQ algorithms and expanding its scope of application for different fingerprint images. (C) 2020 Society for Imaging Science and Technology.
机译：指纹质量评估通常用于评估从指纹传感器获得的图像的质量，有效的指纹质量评估方法对于建立高性能生物识别系统至关重要。指纹质量评估的使用有助于提高指纹登记和用户满意度的准确性。 NIST指纹图像质量（NFIQ）是一种流行的指纹质量评估算法;然而，它无法为从移动设备传感器获得的某些部分指纹图像提供高质量的评估。在本研究中，检查了综合纹理和几何特征的混合指纹评估框架。通过框架获得的最终质量评估值高于使用NFIQ获得的最终质量评估值，有效地提高现有NFIQ算法的性能并扩展其对不同指纹图像的应用范围。 （c）2020年影像科技协会。

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