Using Neural Networks and Self-Organizing Maps for Image Connecting

被引:0
|
作者
Yi Ding
Tianjiang Wang
Xian Fu
机构
[1] School of Computer Science and Technology Huazhong University of Science and Technology,
[2] College of Computer Science and Technology Hubei Normal University,undefined
来源
Cognitive Computation | 2013年 / 5卷
关键词
Neural network; Image connecting; SOM;
D O I
暂无
中图分类号
学科分类号
摘要
This paper addresses the problem of connecting a sequence of images acquired by a camera rotating about its center. A novel method is introduced using neural networks. The algorithm finds the major overlapping area in the images to be connected using the neural network and then joins the images. The inputs to the network are edge detected images created by applying an algorithm on the original images. The paper presents a theoretical and computational investigation into connecting any two given images using a Self-Organizing Map (SOM). Simulation results demonstrate that self-organizing neural networks can be efficiently used for this purpose.
引用
收藏
页码:13 / 18
页数:5
相关论文
共 50 条
  • [1] Using Neural Networks and Self-Organizing Maps for Image Connecting
    Ding, Yi
    Wang, Tianjiang
    Fu, Xian
    [J]. COGNITIVE COMPUTATION, 2013, 5 (01) : 13 - 18
  • [2] Segmentation of the CT image using self-organizing neural networks
    Martinovic, Marko
    Stoic, Antun
    Kis, Darko
    [J]. TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2008, 15 (04): : 23 - 28
  • [3] Organizing spectral image database using Self-Organizing Maps
    Kohonen, O
    Jääskeläinen, T
    Hauta-Kasari, M
    Parkkinen, J
    Miyazawa, K
    [J]. JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY, 2005, 49 (04) : 431 - 441
  • [4] SOMDNCD: Image Change Detection Based on Self-Organizing Maps and Deep Neural Networks
    Xiao, Ruliang
    Cui, Runxi
    Lin, Mingwei
    Chen, Lifei
    Ni, Youcong
    Lin, Xinhong
    [J]. IEEE ACCESS, 2018, 6 : 35915 - 35925
  • [5] Spam review detection using self-organizing maps and convolutional neural networks
    Neisari, Ashraf
    Rueda, Luis
    Saad, Sherif
    [J]. COMPUTERS & SECURITY, 2021, 106
  • [6] Defensive Islanding Using Self-Organizing Maps Neural Networks and Hierarchical Clustering
    Mahdi, Mohammed
    Genc, Istemihan
    [J]. 2015 IEEE EINDHOVEN POWERTECH, 2015,
  • [7] Modelling of anaerobic digestion using self-organizing maps and artificial neural networks
    Holubar, P
    Zani, L
    Hager, M
    Fröschl, W
    Radak, Z
    Braun, R
    [J]. WATER SCIENCE AND TECHNOLOGY, 2000, 41 (12) : 149 - 156
  • [8] Local modeling using self-organizing maps and single layer neural networks
    Fontenla-Romero, O
    Alonso-Betanzos, A
    Castillo, E
    Principe, JC
    Guijarro-Berdiñas, B
    [J]. ARTIFICIAL NEURAL NETWORKS - ICANN 2002, 2002, 2415 : 945 - 950
  • [9] Using artificial neural networks and self-organizing maps for detection of airframe icing
    Johnson, MD
    Rokhsaz, K
    [J]. JOURNAL OF AIRCRAFT, 2001, 38 (02): : 224 - 230
  • [10] Video and Image Processing with Self-Organizing Neural Networks
    Garcia-Rodriguez, Jose
    Dominguez, Enrique
    Angelopoulou, Anastassia
    Psarrou, Alexandra
    Jose Mora-Gimeno, Francisco
    Orts, Sergio
    Manuel Garcia-Chamizo, Juan
    [J]. ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2011, PT II, 2011, 6692 : 98 - 104