具有强光照波动容忍度的人脸图像识别方案

Kenji Matsuo, M. Hashimoto, A. Koike
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引用次数: 0

摘要

在本文中,我们提出了一种对光照环境变化具有强容忍度的人脸识别方案。目前带有照相设备的手机的普及使得无需额外设备就可以对面部图像进行生物识别认证成为可能。然而,通过手机拍摄的人脸图像会受到光照环境的影响,因为手机在室内和室外都可以无限制地使用。因此,最严重的问题是光照波动降低了其识别精度。我们提出的方案很简单。该方案利用光照规范空间,创建一个包含各种光照元素的虚拟子空间,而无需在不同环境下实际拍摄多张人脸图像。仿真结果表明,与传统子空间方案相比,该方案不仅具有较低的验证等错误率,而且具有较高的识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A face image recognition scheme with strong tolerances to lighting fluctuations
In this paper, we propose a face recognition scheme that has strong tolerances to changes in the lighting environment. The current spread of cellular phones with camera devices has made biometric certification of face images possible, without adding extra devices. However, face images taken via cellular phones are fluctuated by lighting environments, because cellular phones are used both indoors and outdoors without limit. Therefore, the most serious problem is that lighting fluctuations decrease its recognition accuracy. Our proposed scheme is very simple. This scheme uses the lighting canonical space and creates a virtual subspace that contains various elements of lighting, without actually taking many face images under different environments. Simulation results show the proposed scheme can achieve not only a lower equal-error-rate of verification, but also higher precision of identification than the conventional subspace scheme.
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