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Overview of Polarimetric Thermal Imaging for Biometrics

机译:极化热成像生物特征概述

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This paper presents an overview of polarimetric thermal imaging for biometrics, focusing on face recognition, with a short discussion on fingerprints and iris. Face recognition has been and continues to be an active area of biometrics research, with most of the research dedicated to recognition in the visible spectrum. However, face recognition in the visible spectrum is not practical for discrete surveillance in low-light and nighttime scenarios. Polarimetric thermal imaging represents an ideal modality for acquiring the naturally emitted thermal radiation from the human face, providing additional geometric and textural details not available in conventional thermal imagery. One of the main challenges lies in matching the acquired polarimetric thermal facial signature to gallery databases containing only visible facial signature, for interoperability with existing government biometric repositories. This paper discusses approaches and algorithms to exploit polarization information, as represented by the Stokes vectors, through feature extraction and nonlinear regression to enable polarimetric thermal-to-visible face recognition. In addition to cross-spectrum feature based approaches, cross-spectrum image synthesis methods are discussed that seek to reconstruct a visible-like image given a polarimetric thermal face image input. Beyond facial biometrics, this paper presents an initial exploration of polarimetric thermal imaging for latent fingerprint acquisition. Latent prints are formed when the oils and sweat from the finger are deposited onto another surface through contact, and are typically collected by first dusting with powder before being imaged and then lifted with adhesive tape. This paper presents polarimetric thermal imagery of latent prints from a nonporous glass surface, acquired without the dusting process. A brief discussion of the utility of polarimetric thermal imaging for iris recognition is also presented.
机译:本文概述了用于生物识别技术的偏振热成像技术,重点是面部识别,并简短讨论了指纹和虹膜。人脸识别一直是并将继续成为生物识别研究的活跃领域,其中大部分研究致力于在可见光谱中进行识别。但是,在弱光和夜间场景中进行离散监视时,在可见光谱中的人脸识别是不实际的。极化热成像代表了一种理想的模态,用于获取人脸自然发出的热辐射,并提供了常规热成像中无法提供的其他几何和纹理细节。主要挑战之一是将获取的极化热面部特征与仅包含可见面部特征的图库数据库进行匹配,以实现与现有政府生物特征信息库的互操作性。本文讨论了利用Stokes向量表示的极化信息的方法和算法,该方法和算法通过特征提取和非线性回归来实现极化热敏可见面部识别。除了基于互谱特征的方法外,还讨论了互谱图像合成方法,该方法试图在给定偏振热面部图像输入的情况下重建类似可见图像的图像。除面部生物识别技术外,本文还介绍了极化热成像技术对潜在指纹采集的初步探索。当手指上的油脂和汗液通过接触而沉积在另一表面上时,便会形成潜在的印记,通常先在成像前先用粉末撒粉,然后再用胶带提起,然后将其收集起来。本文介绍了无尘玻璃表面上潜像的偏振热成像,该成像无需进行除尘处理即可获得。还简要介绍了偏振热成像在虹膜识别中的应用。

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