Target recognition technology based on wavelet transform

被引:0
|
作者
Chen, Yu [1 ]
Song, Yulong [2 ]
Huo, Furong [1 ]
机构
[1] Changchun Univ Sci & Technol, Sch Optoelect Engn, Changchun 130022, Peoples R China
[2] Changchun Inst Opt, Fine Mech & Phys, Changchun 130022, Peoples R China
关键词
Pattern recognition; Joint transform correlator; Target recognition; Wavelet transform; cluttered background;
D O I
10.4028/www.scientific.net/AMM.651-653.534
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Hybrid optoelectronic joint transform correlator is a very effecitve tool to recognize a target, which has important application in military and industry field. However, in actual applications, under some situations, such as complex target background or insufficient contour information etc., the intensity of correlation peaks will be weak. Sometimes, the weak intensity of correlation peaks can not be recognized by joint transform correlator. Wavelet transform is adopted to process the joint target image. The principles of joint transform correlator and wavelet transform are given in this paper. As an actual example, a tank target is adopted to test the feasibility and effectiveness of this method. From computer simulation, we can get good experimental effect. After wavelet transform of joint target image, the intensity of correlation peaks has been increased obviously. Optical experiments confirm the feasibility and effectiveness of this method further. Amounts of experiments prove wavelet transform can extract the target contour effectively. Based on the principle of the proposed algorithm, the target recognizing rate can be increased to a higher level.
引用
收藏
页码:528 / +
页数:2
相关论文
共 50 条
  • [1] Target recognition in clutter scene based on wavelet transform
    Chen, Fanghan
    Wang, Wensheng
    [J]. OPTICS COMMUNICATIONS, 2009, 282 (04) : 523 - 526
  • [2] Artificial target recognition based on wavelet transform and Holder constant
    [J]. Hongwai Yu Haomibo Xuebao, 5 (358-362):
  • [3] Target Feature Recognition Based on Wavelet Transform and CNN-SVM
    Dong, Tianzhen
    Qi, Xiao
    Li, Wenju
    Qin, Mingyang
    [J]. 2018 11TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1, 2018, : 347 - 350
  • [4] Software package based on the continuous wavelet transform for automatic target recognition
    Le-Tien, T
    Nguyen, TD
    [J]. PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2, 1998, : 1287 - 1290
  • [5] Faint target detection based on wavelet transform and data fusion technology
    Gu, Jing-Liang
    Wan, Min
    Zhang, Wei
    Zheng, Jie
    [J]. Qiangjiguang Yu Lizishu/High Power Laser and Particle Beams, 2005, 17 (07): : 983 - 986
  • [6] Automatic Target Recognition Based on Discrete Wavelet Transform and Principal Component Analysis
    Xu, Ning
    Jia, Ping
    [J]. 2012 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING (WICOM), 2012,
  • [7] Target detection based on wavelet transform
    Qiu, Guoqing
    Luo, Pan
    Yang, Haijing
    Wei, Yating
    Wang, Yantao
    [J]. 2018 CHINESE AUTOMATION CONGRESS (CAC), 2018, : 3930 - 3933
  • [8] Research on wavelet-based image target detection & recognition technology
    Wang A-min
    Gao Ying
    Wang Feng-hua
    Guo Shu-xia
    [J]. MATERIALS, TRANSPORTATION AND ENVIRONMENTAL ENGINEERING, PTS 1 AND 2, 2013, 779-780 : 1689 - +
  • [9] Facial Recognition Based on Wavelet Transform
    Zhang, Ruolin
    Ding, Jian
    [J]. 2012 WORLD AUTOMATION CONGRESS (WAC), 2012,
  • [10] Wavelet Transform Based Fingerprint Recognition
    Caliskan, Abidin
    Ertugrul, Omer Faruk
    [J]. 2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2015, : 1481 - 1484