• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Mathematics of data/image pattern coding, compression, and encryption with applications XIII >Edge Pattern Analysis for Edge Detection and Localization
【24h】

Edge Pattern Analysis for Edge Detection and Localization

机译：用于边缘检测和定位的边缘图案分析

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Edge detection process plays an important role in image processing, and at its most basic level classifies image pixels into edges and non-edge pixels. The accuracy of edge detection methods in general image1 processing determines the eventual success or failure of computerized analysis procedures which follow the initial edge detection determinations. In view of this downstream impact on pattern processing, considerable care should be taken to improve the accuracy of the front-end edge detection. In general, edges would be considered as abrupt changes or discontinuity in intensity of an image. Therefore, most of edge detection algorithms are designed to capture signal discontinuities but the spatial character of especially complex edge patterns has not received enough attention. Edges can be divided into basic patterns such as ramp, impulse, and st.ep: different types have different shapes and consequent mathematical properties. In this paper, the behavior of various edge patterns, under different order derivatives in the discrete domain, are examined and analyzed to determine how to accurately detect and localize these edge patterns, especially reducing double edge response1 that is one important drawback to the derivative method. General rules about the depiction of edge patterns are proposed. Asides from the ideal patterns already described, other pattern types, such as stair and roof, are examined to broaden the initial analysis. Experiments conducted to test my propositions support the idea that edge patterns are instructive in enhancing the accuracy of edge detection and localization.
机译：边缘检测过程在图像处理中起着重要作用，并且在最基本的层次上将图像像素分为边缘像素和非边缘像素。常规image1处理中边缘检测方法的准确性决定了遵循初始边缘检测确定的计算机分析程序的最终成败。考虑到下游对图案处理的影响，应采取相当的措施来提高前端边缘检测的准确性。通常，边缘将被视为图像强度的突然变化或不连续。因此，大多数边缘检测算法被设计为捕获信号不连续性，但是特别复杂的边缘模式的空间特性并未引起足够的重视。边缘可以分为基本模式，例如斜坡，脉冲和st.ep：不同的类型具有不同的形状和相应的数学属性。本文研究并分析了离散域中不同阶导数下各种边缘图案的行为，以确定如何准确检测和定位这些边缘图案，尤其是减少双边缘响应1，这是导数方法的一个重要缺点。提出了关于边缘图案描绘的一般规则。除了已经描述的理想图案之外，还检查了其他图案类型，例如楼梯和屋顶，以扩大初始分析范围。为验证我的命题而进行的实验支持这样的观点，即边缘模式对于提高边缘检测和定位的准确性具有指导意义。

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