首页> 外文会议>2010 IEEE Conference on Robotics Automation and Mechatronics >Contour feature detection based on Gestalt rule and maximum entropy of neighborhood
【24h】

Contour feature detection based on Gestalt rule and maximum entropy of neighborhood

机译:基于格式塔规则和邻域最大熵的轮廓特征检测

获取原文

摘要

A novel approach is presented to detect contour of object. Firstly, the zero-cross operator to imitate the visual receptive field is used to detect edge of image. Secondly, facing the large amount of noise in complex background, the neighborhood description operator is designed, and the neighborhood information of interesting point is analyzed as well. Then the contours of objects are acquired by combining with the Gestalt psychology theories. During the process, the maximum entropy and state transition probability of feature mode are introduced to ensure the effectiveness of contour detection. Finally, the experiments verify the validity of the proposed method.
机译:提出了一种新颖的方法来检测物体的轮廓。首先,使用过零运算符模仿视觉感受力来检测图像的边缘。其次,面对复杂背景下的大量噪声,设计了邻域描述算子,并对感兴趣点的邻域信息进行了分析。然后结合格式塔心理学理论获得物体的轮廓。在此过程中,引入了特征模式的最大熵和状态转移概率,以确保轮廓检测的有效性。最后,实验验证了该方法的有效性。

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