Image structure representation and classification based on recursive neural network

doi:10.3724/SP.J.1087.2005.0766

Journal of Computer Applications ›› 2005, Vol. 25 ›› Issue (04): 766-768.DOI: 10.3724/SP.J.1087.2005.0766

• Graphics and image processing • Previous Articles Next Articles

Image structure representation and classification based on recursive neural network

QU Shen¹,WANG Qing¹,CHI Zhe-ru²

1.School of Computer Science,Northwestern Polytechnical University,Xi’an Shaanxi 710072,China; 2.Department of Electronics and Information Engineering,Hong Kong Polytechnic University,Hong Kong,China

Online:2005-04-01 Published:2005-04-01

基于迭代神经网络的图像结构表示和分类

屈伸¹，王庆¹，池哲儒²

1.西北工业大学计算机学院； 2.香港理工大学电子与资讯工程学系

基金资助:
国家自然科学基金资助项目(60403008);;陕西省自然科学基金资助项目

Abstract

Abstract:

由于缺少结构化的表示,基于内容的图像分类存在一定的问题,据此提出了一种基于迭代神经网络的自然图像表示和分类的方法。利用Berkeley分割算法将图像分割成不同的区域,采用基于人工的多叉树或基于邻接区域的二叉树的方法进行区域合并,同时提取区域统计特征,得到图像的树型结构表示。根据BPTS算法对网络进行训练,训练好的网络就具备了图像分类的功能。实验结果表明,基于迭代神经网络的结构表示和分类方法具有很强的结构学习能力,同时人工生成的多叉树涵盖更多的语义信息且能得到较好的分类结果。

Key words: BPTS, image segmentation, region mergence, recursive neural network

摘要：

关键词: BPTS, 图像分割, 区域合并, 迭代神经网络

CLC Number:

TP391.41

QU Shen,WANG Qing,CHI Zhe-ru. Image structure representation and classification based on recursive neural network[J]. Journal of Computer Applications, 2005, 25(04): 766-768.

屈伸，王庆，池哲儒. 基于迭代神经网络的图像结构表示和分类[J]. 计算机应用, 2005, 25(04): 766-768.

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Image structure representation and classification based on recursive neural network

基于迭代神经网络的图像结构表示和分类

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