Automatic face recognition via wavelets and mathematical morphology
Automatic face recognition via wavelets and mathematical morphology
复制标题
通过小波和数学形态学自动人脸识别
DOI：
10.1109/icpr.1996.546715
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发表时间：
1996
期刊：
影响因子：
--
通讯作者：
Rafal Foltyniewicz
中科院分区：
文献类型：
--
作者：
Rafal Foltyniewicz
提出了一种新的人脸自动识别与验证方法。建议的方法基于两个阶段的过程。在第一步中，使用小波分解技术或形态非线性滤波来增强人脸的内在特征，减少深度旋转、面部表情变化、眼镜和光照条件的影响。预处理后的图像包含了人脸识别的所有必要信息，并且具有快速的学习收敛性、良好的泛化性和少量可调权值的改进高阶神经网络是下一步学习的主题。该系统不是基于任务依赖的几何特征提取，因此可以很容易地应用于其他图像识别任务。
Presents a new method for automatic face recognition and verification. The proposed approach is based on a two stage process. In the first step a wavelet decomposition technique or morphological nonlinear filtering is used to enhance intrinsic features of a face, reduce the influence of rotation in depth, changes in facial expression, glasses and lighting conditions. Preprocessed images contain all the essential information for the discrimination between different faces and are next a subject for learning by a modified high order neural network which has rapid learning convergence, very good generalization properties and a small number of adjustable weights. The system is not based on task dependent geometric feature extraction, and as such, it can be easily applied to other image recognition tasks.
影响因子：
4
作者：
BRUCE, V;YOUNG, A
通讯作者：
YOUNG, A