基于子波分解的多通道神经网络纹理分割方法
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TP391.41 TN919.8

基金项目:

国防预研基金,国家自然科学基金


A WAVELET TRANSFORMATION BASED MULTICHANNEL NEURAL NETWORK METHOD FOR TEXTURE SEGMENTATION
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    描述了一种体现多通道滤波技术的神经网络纹理分割方法,决策神经网络(DBN)可提高纹理分类的精度,同时纹理的子波变换降低了图像数据间的相关性,提高了网络的学习效率,实验表明本文提出孤方法分类误差较低,获得了令人满意的纹理分割效果。

    Abstract:

    A neural network texture segmentation method, in which multichannel filtering is embodied, was proposed. Multichannel filtering technology is a very effective method for texture segmentation. Instead of using a general filter bank, the texture feature extraction and classification tasks were performed in this paper by the same unified neural network. Decision based neural network was adopted to improve the accuracy of classification. Wavelet transformation of texture was used to decrease the correlation of texture data and increase the efficiency of networks learning. Experiments show that the proposed method achieves lower error rates than other methods and a satisfactory result is obtained.

    参考文献
    相似文献
    引证文献
引用本文

张军 戚飞虎.基于子波分解的多通道神经网络纹理分割方法[J].红外与毫米波学报,1998,17(1):54~60]. ZHANG Jun QI Fei Hu. A WAVELET TRANSFORMATION BASED MULTICHANNEL NEURAL NETWORK METHOD FOR TEXTURE SEGMENTATION[J]. J. Infrared Millim. Waves,1998,17(1):54~60.]

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:1997-06-17
  • 录用日期:
  • 在线发布日期:
  • 出版日期:
文章二维码