Robust method for ship recognition based on ISAR imaging using 3D model

被引:2
|
作者
Xie, Sudao D. [1 ,2 ]
Pan, M. Y. [1 ,2 ]
Li, D. S. [1 ,2 ]
机构
[1] Nanjing Res Inst Elect Technol, Nanjing, Jiangsu, Peoples R China
[2] CETC, Key Lab IntelliSense Technol, Nanjing, Jiangsu, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 20期
关键词
D O I
10.1049/joe.2019.0315
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study develops a robust method for ship target recognition, based on inverse synthetic aperture radar (ISAR) image matching with the template of 3D model. To deal with the difficulty of building template lib, the authors develop to use CAD model instead of the live radar data, which can be projected to the range-Doppler plane at any angle. In the study, the method of matching between the observed ISAR image and candidate target image of model is also proposed, including feature extraction and scoring for recognition. In addition, influences of estimation accuracy for projection are analysed and simulated. Finally, recognition results obtained with simulated data are provided to verify the effectiveness of the proposed approach.
引用
收藏
页码:6777 / 6780
页数:4
相关论文
共 50 条
  • [41] Recognition of 3D Rotating Ship Based on Mix-CV-CNN
    Zhang Y.
    Hua Q.-L.
    Jiang Y.-C.
    Xu D.
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2022, 50 (05): : 1042 - 1049
  • [42] Improved 3D ISAR Using Linear Arrays
    Pui, Chow Yii
    Ng, Brian
    Rosenberg, Luke
    Cao, Tri-Tan
    2022 23RD INTERNATIONAL RADAR SYMPOSIUM (IRS), 2022, : 196 - 201
  • [43] Face Recognition Analysis Using 3D Model
    Khan, Muhammad Sajid
    Jehanzeb, Muhammad
    Babar, Muhammad Imran
    Faisal, Shah
    Ullah, Zabeeh
    Amin, Siti Zulaikha Binti Mohamad
    EMERGING TECHNOLOGIES IN COMPUTING, ICETIC 2018, 2018, 200 : 220 - 236
  • [44] Statistical recognition of 3D objects using integral imaging
    Cuong Manh Do
    MACHINE INTELLIGENCE AND BIO-INSPIRED COMPUTATION: THEORY AND APPLICATIONS VII, 2013, 8751
  • [45] Model-based Recognition of 3D Objects using Intersecting Lines
    Truong, Hung Q.
    Lee, Sukhan
    Jang, Seok-Woo
    2008 IEEE INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INTEGRATION FOR INTELLIGENT SYSTEMS, VOLS 1 AND 2, 2008, : 88 - 92
  • [46] Model-based 3D object recognition using Bayesian indexing
    Yi, JH
    Chelberg, DM
    COMPUTER VISION AND IMAGE UNDERSTANDING, 1998, 69 (01) : 87 - 105
  • [47] Robust 3D face recognition using learned visual codebook
    Zhong, Cheng
    Sun, Zhenan
    Tan, Tieniu
    2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8, 2007, : 2371 - +
  • [48] Robust 3D Face Recognition using Learn Correlative Features
    Ming, Yue
    Ruan, Qiuqi
    Wang, Xueqiao
    Mu, Meiru
    2010 IEEE 10TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS (ICSP2010), VOLS I-III, 2010, : 1382 - 1385
  • [49] Pose robust 3D face recognition using the RBFN feature
    Yang, Ukil
    Sohn, Kwanghoon
    PROCEEDINGS OF THE SEVENTH IASTED INTERNATIONAL CONFERENCE ON VISUALIZATION, IMAGING, AND IMAGE PROCESSING, 2007, : 235 - +
  • [50] Robust Model-Based 3D/3D Fusion Using Sparse Matching for Minimally Invasive Surgery
    Neumann, Dominik
    Grbic, Sasa
    John, Matthias
    Navab, Nassir
    Hornegger, Joachim
    Ionasec, Razvan
    MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION (MICCAI 2013), PT I, 2013, 8149 : 171 - 178