首页> 外文会议>Visual Communications and Image Processing 2005 pt.2 >Gradient-based image segmentation for face recognition robust to directional illumination
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Gradient-based image segmentation for face recognition robust to directional illumination

机译:基于梯度的图像分割对方向照明具有鲁棒性

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Non-frontal illumination of objects may cause specular reflections and strong self-shadowing. Those phenomena change the appearance of objects to such an extent that they may not be recognized properly. We propose a method to automatically discard the areas of the image which are degraded beyond recovery by adverse illumination conditions. The method is based on a comparison between local variances of image gradient and is computationally efficient. We show that proposed method, implemented with a face verification system based on local DCTmod2 features and a GMM classifier, reduces total recognition errors in the presence of changing directional illumination conditions. Consequently, we show that proposed segmentation method can be used as an automatic estimator of mismatch between the illumination conditions present during the acquisition of training and testing images. We propose an adaptive thresholding scheme that uses the mismatch estimate to further reduce the recognition error.
机译:物体的非正面照明可能会导致镜面反射和强烈的自阴影。这些现象会改变物体的外观,以致无法正确识别它们。我们提出一种方法来自动丢弃由于不利的照明条件而退化到无法恢复的图像区域。该方法基于图像梯度的局部方差之间的比较,并且计算效率高。我们表明,所提出的方法由基于局部DCTmod2特征的人脸验证系统和GMM分类器实现,可在方向照明条件不断变化的情况下减少总识别错误。因此,我们表明,提出的分割方法可以用作在训练和测试图像的获取过程中出现的照明条件之间不匹配的自动估计器。我们提出一种自适应门限方案,该方案使用失配估计来进一步减少识别误差。

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