期刊文献+

基于TMS320DM6446和TVP5158的虹膜识别系统 被引量:1

Iris Recognition System Based on TMS320DM6446 and TVP5158
在线阅读 下载PDF
导出
摘要 设计并实现了一套基于TMS320DM6446和TVP5158的虹膜识别系统。硬件设计采用TMS320DM6446+TVP5158+NAND FLASH架构,以较低成本实现了两路虹膜图像的同时采集与处理。软件设计基于CodecEngine架构,ARM端负责视频采集、结果显示和数据库的管理,DSP端专注于虹膜识别核心算法,通过图像采集、虹膜定位、特征提取与特征匹配4个步骤来实现虹膜识别。该系统充分利用TMS320DM6446强大的图像处理能力,经过C语言级别和汇编语言级别的优化,该系统能获得较好的识别效果。 An iris recognition system based on TMS320DM6446 and TVP5158 is introduced. The hardware design is based on the TMS320DM6446 + TVP5158 + NAND FLASH architec- ture, which achieves the low-cost dual-iris image acquisition. The software design is based on the Codec Engine framework, where the ARM side is responsible for image acquisition, database management and user interface, and the DSP side focuses on the core algorithm, con- sisting of image evaluation, iris localization, feature extraction, and code matching. The sys- tem takes full advantage of the powerful image processing capability of TMS320DM6446. After code optimization under the C level and the assembly level, the system can obtain the high ac- curacy with the fast identification speed.
出处 《数据采集与处理》 CSCD 北大核心 2012年第6期658-664,共7页 Journal of Data Acquisition and Processing
关键词 虹膜识别 GABOR小波 达芬奇系统 iris recognition Gabor wavelets Davinci system
  • 相关文献

参考文献5

  • 1Chen C, Hong C, Chuang H. Efficient auto-focus al- gorithm utilizing discrete difference equation predic- tion model for digital still cameras [J]. IEEE Trans- actions on Consumer Electronics, 2006, 4 (52); 1135-1143.
  • 2Daugman J. Recognition people by their iris patterns [J]. Information Security Technical Report, 1998, 3 (1): 33-39.
  • 3Wildes R. Iris recognition: an emerging biometric technology [J]. Proceeding of the IEEE, 1997, 85 (9) : 1348-1363.
  • 4Ma L, Tieniu T, Yunhong W, etal. Efficient iris recognition by characterizing key local variations[J]. IEEE Transactions on Signal Processing, 2004:13 (6) : 739-750.
  • 5Daugman J. Probing the uniqueness and randomness of iriscodes., results from 200 billion iris pair com- parisons [J]. Proceedings of the IEEE, 2006, 94 (11) : 1927-1935.

同被引文献18

  • 1李武军,王崇骏,张炜,陈世福.人脸识别研究综述[J].模式识别与人工智能,2006,19(1):58-66. 被引量:108
  • 2李江,郁文贤,匡刚要,宋海娜.红外图像人脸识别方法[J].国防科技大学学报,2006,28(2):73-76. 被引量:16
  • 3彭启琮.达芬奇技术[M].北京:电子工业出版社,2008,9:116-121.
  • 4Zhang Xiaozheng, Gao Yongsheng. Face recognition across pose: A review[J]. Pattern Recognition, 2009, 42(11): 2876- 2896.
  • 5Buciu I. Overview of face recognition techniques[J]. Journal of Electrical and Electronics Engineering, 2008, 1(1): 173- 176.
  • 6Hizem W, Allano L, Mellakh A, et al. Face recognition from synchronised visible and near-infrared images[J]. Signal Pro- cessing, 2009, 3(4): 282-288.
  • 7Li S Z. A highly accurate and fast face recognition system[J]. Computer Vision, 2005, 12(2): 28- 33.
  • 8Tan Xiaoyang, Bill T. Enhanced local texture feature sets for face recognition under difficult lighting conditions[J]. IEEE Transactions on Image Processing, 2010, 19(6): 1635-1650.
  • 9Takano T, Fukumizu Y, Yamauchi H. Face recognition system using gabor pseudo-fisherface method for embedded LSI ap- plications[J]. Journal of Signal Processing, 2009, 13(4) : 343-346.
  • 10Yang M, Crenshaw J, Augustine B, et al. Adaboost-based face detection for embedded systems[J]. Computer Vision and Image Understanding, 2010, 114(11) :1116- 1125.

引证文献1

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部