首页> 外文会议>Symposium on Photonics and Optoelectronics >A PCNN-based Edge Detection Algorithm for Rock Fracture Images
【24h】

A PCNN-based Edge Detection Algorithm for Rock Fracture Images

机译:基于PCNN的岩石骨折图像边缘检测算法

获取原文
获取外文期刊封面目录资料

摘要

Image segmentation has attracted the attention of researchers for many decades. Different approaches have been developed in order to find out the solution in many different segmentation situations. In this paper a novel method for rock fracture image using improved pulse coupled neural networks (PCNN) is presented. We apply progressive scan and region marked method to detect accurate edges of rock fracture images, the experiment results show that the proposed method can be used as a new image edge detection method. Compared to the traditional edge detection algorithms such as Canny operator and the other edge detection operators (e.g. vector gradient and MY), the proposed method can easily obtain the rock fracture images' orientations, curvatures, lengths, apertures and other useful information.
机译:图像分割已经吸引了几十年来研究人员的注意。已经开发了不同的方法,以便在许多不同的分段情况下找出解决方案。本文提出了一种利用改进的脉冲耦合神经网络(PCNN)的岩石骨折图像的新方法。我们应用渐进式扫描和区域标记方法以检测岩石骨折图像的准确边缘,实验结果表明,所提出的方法可以用作新的图像边缘检测方法。与传统的边缘检测算法相比,例如Canny操作员和其他边缘检测操作员(例如矢量梯度和我的),所提出的方法可以容易地获得岩石骨折图像的方向,曲率,长度,孔径和其他有用信息。

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