[1]苏光大.多技术合力的人脸识别系统设计[J].智能系统学报,2009,4(06):471-474.[doi:doi:10.3969/j.issn.1673-4785.2009.06.001]
 SU Guang-da.Face recognition system designed to integrate multiple techniques[J].CAAI Transactions on Intelligent Systems,2009,4(06):471-474.[doi:doi:10.3969/j.issn.1673-4785.2009.06.001]
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多技术合力的人脸识别系统设计(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第4卷
期数:
2009年06期
页码:
471-474
栏目:
出版日期:
2009-12-25

文章信息/Info

Title:
Face recognition system designed to integrate multiple techniques
文章编号:
1673-4785(2009)06-0471-04
作者:
苏光大
清华大学 电子工程系,北京 100084
Author(s):
SU Guang-da
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
关键词:
人脸识别Gabor滤波图像并行处理
Keywords:
face recognition Gabor transform image parallel processing
分类号:
TP391.4
DOI:
doi:10.3969/j.issn.1673-4785.2009.06.001
文献标志码:
A
摘要:
人脸识别系统结构复杂,也包含了多种技术.从多个角度阐述了多技术合力的人脸识别系统设计方法,内容涉及人脸图像采集、人脸识别算法、并行处理、综合系统集成4个部分.多技术合力的人脸识别系统设计方法体现了速度与智能化相结合的优势,也体现了系统的完备性和性能的互补性.给出了该方法在人脸识别率和识别速度上达到的性能指标,并给出了所设计的人脸识别系统的部分突出应用.
Abstract:
Face recognition systems usually have complicated structures and integrate many techniques. In this paper, the design of a face recognition system that combines various technologies was explained from different perspectives, including facial image capture, face recognition algorithms, parallel processing, and system integration. Multitechnique integration reflects the advantages of combining hardware speed with artificial intelligence, as well as the completeness and complementary performance of the proposed face recognition system. Experiments with the suggested system showed improvements in recognition rate and recognition speed. Finally, some special applications of this system were presented.

参考文献/References:

[1]苏光大. 图像并行处理技术[M]. 北京: 清华大学出版社,2002:20-23.
[2]TURK M,PENTLAND A. Face recognition using eigenfaces[C]//Proc IEEE CVPR’91.Lahaina,aui,USA,1991:586-591.
[3]SU Guangda, ZHENG Cuiping, DING Rong,DU Cheng. MMPPCA face recognition method[J]. Electronics Letters,2002, 38(25):1654-1656.
[4]DAUGMAN J G.Two-dimensional spectral analysis of cortical receptive field profile[J]. Vision Research, 1980, 20:847-856.
[5]XIANG Yan, SU Guangda. Multiparts and multi-feature fusion in face verification[C]//2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Anchorage,USA, 2008:102-107.
[6]LEE T. Image representation using 2D Gabor wavelets[J]. IEEE Trans on Pattern Analysis and Machine Intelligence,1996,18(10): 959-971.
[7]MENG Kai, SU Guangda, LI Congcong, FU Bo, ZHOU Jun. A high performance face recognition system based on a huge face database[C]//2005 International Conference on Machine Learning and Cybernetics. Guangzhou, China, 2005:5159-5164.
[8]SU G D, SHANG Y.A multimodal and multistage face recognition method for simulated portrait[C]//Proceedings of the 18th International Conference on Pattern Recognition (ICPR2006).Hong Kong,China,2006:1013-1017.

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备注/Memo

备注/Memo:
收稿日期:2009-03-24.
基金项目:国家“十一五”科技支撑计划资助项目(2006BAK08B07).
作者简介:
苏光大,男,1948年生,教授,博士生导师,目前主要研究方向为图像识别(人脸识别、指纹识别)和高速图像处理.提出了图像邻域计算理论和视频图像1∶1采样理论.研制成功的人脸识别系统、计算机人像组合系统、模糊图像复原系统在我国公安办案工作中广泛应用,破获了大量的刑事案件.研制成功的人脸识别技术成功用于2008年北京奥运会;NIPC3邻域图像并行计算机,在邻域图像处理的速度上达到了国际最高水平.获发明创业奖和发明展金奖,6次获省部级科技成果奖,获5项国家发明专利,3次获清华大学先进工作者称号.发表学术论文120余篇,著有《微机图像处理系统》、《图像并行处理技术》2部专著 .
更新日期/Last Update: 2010-02-17