Image normalization method for face identification under difficult lighting conditions

M. Smiatacz
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引用次数: 4

Abstract

Difficulties related to poor illumination conditions are one of the main reasons for which many face identification algorithms fail in real-life situations. The paper presents a new method for image normalization, based on simple techniques such as binarization and histogram equalization, that effectively removes the shadows and provides illumination invariants that significantly improve the accuracy of face identification process. During experiments the proposed method outperformed the state of the art approach based on anisotropic smoothing.
困难光照条件下人脸识别的图像归一化方法
光照条件差是许多人脸识别算法在现实生活中失败的主要原因之一。本文提出了一种基于二值化和直方图均衡化等简单技术的图像归一化新方法,该方法能够有效地去除阴影并提供光照不变量,从而显著提高人脸识别过程的准确性。在实验中,该方法优于当前基于各向异性平滑的方法。
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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