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Overview of Polarimetric Thermal Imaging for Biometrics

机译:Bimetrics Polariemetric热成像概述

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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Bigetric热成像的生物识别,专注于面部识别,讨论了指纹和虹膜。面部识别已经并持续成为生物识别研究的活跃领域,大部分研究都致力于在可见光谱中识别。然而,可见光谱中的人脸识别对于低光和夜间场景中的离散监视是不实际的。偏振热成像表示用于获取来自人脸的自然发射的热辐射的理想方式,提供额外的几何和纹理细节,不可用在传统的热图像中。其中一个主要挑战在于将所获得的Polarimetric热面部签名与仅包含可见面部签名的Gallery数据库相匹配,用于与现有的政府生物识别存储库的互操作性。本文讨论了利用极化信息的方法和算法,其通过特征提取和非线性回归来实现斯托克斯向量,以实现极化热对可见的面部识别。除了基于跨频谱特征的方法之外,讨论了跨频谱图像合成方法,其寻求重建定位的热面图像输入来重建可见的图像。除了面部生物识别学之外,本文提出了对潜在指纹采集的偏振热成像的初步探索。当从手指沉积到另一个表面上通过接触沉积在另一个表面上时形成潜在的印刷,并且通常通过在成像之前通过首先用粉末进行粉末收集,然后用胶带抬起。本文介绍了从无孔玻璃表面的潜在印花的偏振热图像,在没有粉尘过程的情况下获得。还介绍了对虹膜识别的偏振热成像的效用。

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