Application notes - Algorithms for Assessing the Quality of Facial Images
Application notes - Algorithms for Assessing the Quality of Facial Images
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DOI：
10.1109/mci.2007.353416
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发表时间：
2007-05
影响因子：
9
通讯作者：
M. Abdel-Mottaleb;M. Mahoor
中科院分区：
文献类型：
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作者：
M. Abdel-Mottaleb;M. Mahoor
在本文中，我们提出了算法来评估受模糊度、光照条件、头部姿势变化和面部表情等因素影响的面部图像质量。我们基于特征脸技术开发了针对受模糊度、光照条件和头部姿势变化影响的图像的人脸识别预测功能。我们还开发了一个针对受面部表情影响的图像的分类器，以评估其特征脸技术识别的质量。我们使用不同面部图像数据库的实验表明，我们的算法能够评估面部图像的质量。这些算法可用于人脸识别系统中的人脸图像质量评估模块。将来，我们将整合不同的图像质量衡量标准，以产生一个表示人脸图像整体质量的单一衡量标准
In this paper, we presented algorithms to assess the quality of facial images affected by factors such as blurriness, lighting conditions, head pose variations, and facial expressions. We developed face recognition prediction functions for images affected by blurriness, lighting conditions, and head pose variations based upon the eigenface technique. We also developed a classifier for images affected by facial expressions to assess their quality for recognition by the eigenface technique. Our experiments using different facial image databases showed that our algorithms are capable of assessing the quality of facial images. These algorithms could be used in a module for facial image quality assessment in a face recognition system. In the future, we will integrate the different measures of image quality to produce a single measure that indicates the overall quality of a face image