Evaluation of image compression algorithms for fingerprint and face recognition systems

W. Funk, M. Arnold, C. Busch, A. Munde
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引用次数: 41

Abstract

A variety of widely accepted and efficient compression methods do exist for still images. To name a few, there are standardised schemes like JPEG and JPEG2000 which are well suited for photorealistic true colour and grey scale images and usually operated in lossy mode to achieve high compression ratios. These schemes are well suited for images that are processed within face recognition systems. In the case of forensic biometric systems, compression of fingerprint images has already been applied in automatic fingerprint identification systems (AFIS) applications, where the size of the digital fingerprint archives would be tremendous for uncompressed images. In these large scale applications wavelet scalar quantization has a long tradition as an effective encoding scheme. This paper gives an overview of the study BioCompress that has been conducted at Fraunhofer IGD on behalf of the Federal Office for Information Security (BSI). Based on fingerprint and face image databases and different biometric algorithms we evaluated the impact of lossy compression algorithms on the recognition performance of biometric recognition systems.
评价指纹和人脸识别系统的图像压缩算法
对于静止图像,确实存在各种被广泛接受和有效的压缩方法。举几个例子,有标准化的方案,如JPEG和JPEG2000,它们非常适合逼真的真彩色和灰度图像,通常在有损模式下运行,以实现高压缩比。这些方案非常适合在人脸识别系统中处理的图像。在法医生物识别系统中,指纹图像的压缩已经应用于自动指纹识别系统(AFIS)中,在这种系统中,未压缩的数字指纹档案的大小将是巨大的。在这些大规模应用中,小波标量量化作为一种有效的编码方案有着悠久的传统。本文概述了Fraunhofer IGD代表联邦信息安全办公室(BSI)进行的研究BioCompress。基于指纹和人脸图像数据库以及不同的生物识别算法,我们评估了有损压缩算法对生物识别系统识别性能的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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