A Fast Infrared Face Recognition System Using Curvelet Transformation

摘要：

In this paper, a fast infrared face recognition system using Curvelet transformation is proposed. Firstly, to get the good performance of infrared face recognition from the biological feature, thermal images are converted into blood perfusion domain by blood perfusion model. Secondly, Curvelet transform has better directional and edge representation abilities than widely used wavelet transformation and other classic transformations. Inspired by these attractive attributes of Curvelets in sparse representation of the images, we introduce the idea of decomposing images into their curvelet subbands to extract the principal representative feature, which saves the computational complexity and storage units. Finally, the nearest neighbor classifier is chosen to get the system recognition result. The experiments illustrate that compared with traditional PCA based systems, the proposed system has better performance and requires fewer computations and memory units.

关键词： infrared face recognition blood perfusion curvelet transformation sparse representation

作者: Zhihua Xie Guodon Liu Shiqian Wu Yu Lu

作者单位: Key Lab of Optic-Electronic and Communication Jiangxi Sciences and Technology Normal University Nanc School of information technology University of Finance and Economics Nanchang, China

会议类型: 国际会议

会议名称: Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)

会议地点: 南昌

会议语种:英文

页码: 801-805

在线出版日期: 2009-05-22（万方平台首次上网日期，不代表论文的发表时间）