A Method of LVQ Network to Detect Vehicle based on Morphology

被引:3
作者
Zhang Xinye [1 ]
An Jubai [1 ]
Yang ZhiFeng [2 ]
机构
[1] Dalian Maritime Univ, Dalian, Peoples R China
[2] Res Inst Commun Peoples Republ China, Beijing, Peoples R China
来源
PROCEEDINGS OF THE 2009 WRI GLOBAL CONGRESS ON INTELLIGENT SYSTEMS, VOL IV | 2009年
关键词
Hi-resolution Satellite Image; Pattern Recognition; LVQ Artificial Neural Network; Morphology; Texture; WEIGHT NEURAL-NETWORKS;
D O I
10.1109/GCIS.2009.18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, the main research is to recognize and classify vehicle on the traffic road in the hi-resolution satellite image. Because the satellite image contains the vehicle characters pixel set and the alike vehicle characters pixel set. So, there are a series of pattern recognition methods from image preprocessing to the LVQ Artificial Neural Network works. The application of Morphology, is the main preprocessing technology in this paper After image is morphologically preprocessed, it makes the pixel matrix more clear and differentiable. and is good for the next step, which is to calculate the preprocessed image texture. According to the gray level and the texture, a vector is built as input of LVQ Artificial Neural Network system, the trained LVQ Artificial Neural Network will give a satisfying outcome. Finally, with these processing, the result images are given. The white vehicle and the black vehicle are obvious. Although there are some errors in the results, by contrast with the origin images; the results still give a good effort of this method
引用
收藏
页码:339 / +
页数:3
相关论文
共 7 条
  • [1] [Anonymous], 2009, PEARSON ED INDIA
  • [2] *FLYTHINK SCI TECH, 2006, NEUR NETW THEOR MATL, P5
  • [3] Gonzalez R.C., 2005, Digital image processing
  • [4] LADAR target detection using morphological shared-weight neural networks
    Khabou, MA
    Gader, PD
    Keller, JM
    [J]. MACHINE VISION AND APPLICATIONS, 2000, 11 (06) : 300 - 305
  • [5] Automatic target detection using entropy optimized shared-weight neural networks
    Khabou, MA
    Gader, PD
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2000, 11 (01): : 186 - 193
  • [6] Morphological shared-weight networks with applications to automatic target recognition
    Won, YG
    Gader, PD
    Coffield, PC
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1997, 8 (05): : 1195 - 1203
  • [7] ZHONGLUO, 2006, PATTERN RECOGNITION