一种基于核密度估计的图像边缘检测方法

计算机科学 ›› 2018, Vol. 45 ›› Issue (6A): 239-241.

一种基于核密度估计的图像边缘检测方法

周建,徐海芹

东华大学信息科学与技术学院上海201620

出版日期:2018-06-20 发布日期:2018-08-03
作者简介:周建(1992-),男,硕士生,主要研究方向为图像处理;徐海芹(1979-),女,副教授,硕士生导师,主要研究方向为智能计算、网络优化、电路进化设计等,E-mail:xuhaiqin@dhu.edu.cn。

Image Edge Detection Method Based on Kernel Density Estimation

ZHOU Jian, XU Hai-qin

College of Information Sciences and Technology,Donghua University,Shanghai 201620,China

Online:2018-06-20 Published:2018-08-03

摘要/Abstract

摘要： 进行图像边缘检测的算法有很多种,其中基于Sobel算子、Laplace算子、Canny算子等的图像边缘检测方法当属经典。但所提方法不同于这些差分算子方法,而是对灰度图像素进行小窗口区域的核密度估计,从而得到一幅核密度图,然后通过核密度图,选择出合适的带宽或阈值来控制图像边缘的检出。实验表明该方法可行且简单快速。

关键词: 带宽, 核密度估计, 图像边缘检测, 阈值

Abstract: There are many algorithms for image edge detection.Among them,the image edge detection algorithms based on Sobel operator,Laplace operator and Canny operator are classic.But the proposed method is different from these differential operator methods.Pixel carries out kernel density estimation in the small window area to obtain a kernel density map.Then the kernel density map is used to select the appropriate bandwidth or threshold to control the image edge detection.Experimental results show that this method is feasible,simple and fast.

Key words: Bandwidth, Image edge detection, Kernel density estimation, Threshold

中图分类号:

TP751

周建,徐海芹. 一种基于核密度估计的图像边缘检测方法[J]. 计算机科学, 2018, 45(6A): 239-241. https://doi.org/

ZHOU Jian, XU Hai-qin. Image Edge Detection Method Based on Kernel Density Estimation[J]. Computer Science, 2018, 45(6A): 239-241. https://doi.org/

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