期刊文献+

一种基于复杂地物背景图像的目标识别方法 被引量:5

Method of target recognition from images based on complex natural scenes
下载PDF
导出
摘要 为解决复杂地物背景目标识别问题,提出一种基于复杂自然场景图像的目标识别方法。首先,进行多视点多尺度目标动态特征描述和目标轮廓特性视图制备;然后,采用灰度级顶帽形态学重构运算对输入图像进行处理,对处理后的图像进行分割,获得感兴趣区;最后,通过感兴趣区轮廓提取和基于Hausdorff距离匹配识别目标。实验结果表明,提出的方法能有效地从复杂自然场景中识别出目标。 A method of target recognition from images based on complex natural scenes is presented.Firstly,multi-scale and multi-view dynamic features are represented,and the contour characteristic views of the target are prepared.Then,an input image is processed using morphological grayscale reconstruction.The processed image is segmented and the regions of interest are obtained.Lastly,the target is recognized by contour extraction for the regions of interest and matching based on Hausdorff distance metric.The experiment results show that the proposed method can effectively recognize the target from complex natural scenes.
出处 《系统工程与电子技术》 EI CSCD 北大核心 2011年第1期13-16,共4页 Systems Engineering and Electronics
基金 国家自然科学基金重点项目(60736010)资助课题
关键词 目标识别 动态特征描述 轮廓匹配 HAUSDORFF距离 target recognition dynamic feature representation contour matching Hausdorff distance
  • 相关文献

参考文献10

二级参考文献67

  • 1安如,王慧麟,徐大新,冯学智,周绍光,何凯.基于影像尺度空间表达与鲁棒Hausdorff距离的快速角点特征匹配方法[J].测绘学报,2005,34(2):101-107. 被引量:3
  • 2邱志敏,李军,葛军,周起勃.基于Hausdorff距离的自动目标识别算法的研究[J].红外技术,2006,28(4):199-202. 被引量:18
  • 3蒋新土,吕岳.基于改进的加权Hausdorff距离的图像匹配[J].计算机应用研究,2007,24(4):182-183. 被引量:9
  • 4Faugeras O, Luong Q, Maybank S. Camera self-calibration: theory and experiments. Proc. of the Second European Conference Computer Vision, Santa Margherita Ligure, Italy, 1992: 321-334.
  • 5Ponce J, Marimont D, Cass, T. Geometric methods for relative reconstruction from weakly calibrated images. Prec. of the IEEE Conference on Robotics and Automation, San Diego, CA, 1994: 1169-1174.
  • 6Robert L, Faugeras O. Relative 3D positioning and 3D convex hull computation from a weakly calibrated stereo pair. Proc. of the International Conference on Computer Vision, Berlin, Germany, 1993: 540-544.
  • 7Patrick G, Luong Q. Projective invariants for vision. Prec. of the SPIE Conference Geometric Methods in Computer Vision Ⅱ, San Diego, California, 1993: 75-86.
  • 8Scharstein D, Szeliski R. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 2002, 47(1): 7-42.
  • 9Ohta Y, Kanade T. Stereo by intra- and inter-scanline search using dynamic programming. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1985, 7(2): 139- 154.
  • 10Gold S, Rangarajan A, Lu CP, et al. New algorithms for 2D and 3D point matching: pose estimation and correspondence. Pattern Recognition, 1998, 31(8): 1019-1031.

共引文献30

同被引文献37

  • 1张义广,丁明跃,周成平.弹道导弹红外成像制导的关键技术[J].制导与引信,2004,25(4):11-14. 被引量:2
  • 2凌伟,王志乾,高峰端.光电测量系统畸变的实时数字校正[J].光学精密工程,2007,15(2):277-282. 被引量:27
  • 3DELISLE G Y, SEBBANI Z, CHARRIER C, et al. A novel approach to complex target recognition using RCS wavelet decomposition[J]. IEEE Antennas and Propagation Magazine, 2005, 47 (1) : 35-55.
  • 4V1VEK E P, SUDHA N. Robust Hausdorff distance measure for face recognition [J]. Pattern Recognition, 2007, 40(2):431-442.
  • 5BUSTOS J P, DONOSO F, GUESALAGA A, et al.Matching radar and satellite images for ship trajectory estimation using the Hausdorff distance [J]. IET Radar Sonar Navig, 2007, 1(1):50-58.
  • 6VIVEK E P, SUDHA N. Gray Hausdorff distance measure for comparing face images [J]. IEEE Transac tions on Information forensics and Security[J]. 2006, 1(3): 342-349.
  • 7Xia Jing, Sun Jiyin, Hui Li. Forward-looking Infrared Im- age Segmentation Using Support Vector Machine based on Feature Extraction [ J ]. International Conference on Elec- trical and Control Engineering,2010:1031-1034.
  • 8刘洋.前视红外地面建筑物自动识别关键技术研究[D].长沙:国防科技大学,2009.
  • 9Milan Sonka, Vaclav Hlavac, RogerBoyle. Image Process- ing, Analy, and Machine Vision [ M ]. Second edition. Pacific Grove, California: Brooks/Cole, a division of Thomson Corporation, 1999. 163-173.
  • 10Rafael C. Gonzales, Richard E. Woods. Digital Image Pro- cessing Second Edition [ M ]. Beijin : Publishing House of Electronics Industry,2005.

引证文献5

二级引证文献24

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