首页> 外文会议>Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09 >Face Recognition Based on Invariant Eigenvectors and Hausdorff Fraction Distance
【24h】

Face Recognition Based on Invariant Eigenvectors and Hausdorff Fraction Distance

机译:基于不变特征向量和Hausdorff分数距离的人脸识别

获取原文

摘要

A method for face recognition based on invariant eigenvectors and Hausdorff Fraction Distance is proposed. With this method, the invariant eigenvectors based on the image edge are firstly extracted. Then by computing the Hausdorff Fraction Distance between the invariant eigenvectors, the process for similarities evaluation is accomplished. Experimental results on the ORL face database validate that the proposed method is invariant to image rotation, minute edge alteration and illumination conditions, and can improve recognition precision and reduce time complexity simultaneously.
机译:提出了一种基于不变特征向量和Hausdorff分数距离的人脸识别方法。用这种方法,首先提取基于图像边缘的不变特征向量。然后,通过计算不变特征向量之间的Hausdorff分数距离,完成相似性评估过程。在ORL人脸数据库上的实验结果证明,该方法在图像旋转,微小边缘变化和照明条件方面是不变的,并且可以同时提高识别精度和降低时间复杂度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号