首页> 外文会议> >Texture analysis for seabed classification: co-occurrence matrices vs. self-organizing maps
【24h】

Texture analysis for seabed classification: co-occurrence matrices vs. self-organizing maps

机译:海床分类的纹理分析:共现矩阵与自组织图

获取原文

摘要

Considers two well-known pattern recognition techniques using texture analysis. The first is the co-occurrence matrix method which relies on statistics and the second is the Kohonen map which comes from the artificial neural networks domain. Both methods are used as feature extraction methods. The extracted feature vectors are fed to a second Kohonen map used as classifier. The authors report briefly some results of their experimental assessment of the merit of each technique when applied to the problem of classifying the seabed from sequences of real images.
机译:考虑使用纹理分析的两种众所周知的模式识别技术。第一种是依靠统计的共现矩阵方法,第二种是来自人工神经网络领域的Kohonen映射。两种方法都用作特征提取方法。提取的特征向量被馈送到用作分类器的第二Kohonen映射。作者简要报告了他们对每种技术的优点进行实验评估的一些结果,这些结果适用于根据真实图像序列对海底进行分类的问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号