摘要
针对传统图像边缘检测算法抑制噪声能力差的问题,提出一种基于直觉模糊集(Intuitionistic Fuzzy Set,IFS)的边缘检测算法。该算法设定了一个表示平坦区域的模板图像,并在图像窗口内构造了一种同时考虑了图像梯度和图像窗口的方差信息的隶属度函数,然后通过计算图像窗口与模板图像之间的模糊直觉散度(Intuitionistic Fuzzy Divergence,IFD)对边缘进行定位和输出。实验结果表明,对于被高斯噪声或均匀噪声严重污染的图像,该算法能够得到较好的检测结果。
As traditional image edge detection algorithms cannot suppress noise well, an edge detection algorithm based on intuitionistic fuzzy set is proposed. This method sets a template that indicates the flat region and in image window constructs a membership function, which considers both gradient and variance information, then the intuitionistic fuzzy divergence is calculated between the template and each image window through the image to locate and output edges.Experimental results show that the proposed algorithm can get good detection results for images seriously contaminated by Gaussian and uniform noise.
出处
《计算机工程与应用》
CSCD
北大核心
2017年第23期6-11,共6页
Computer Engineering and Applications
基金
国家重点研发计划项目子课题(No.2016YFC0101602)
山西省回国留学人员科研资助项目(No.2016-085)
山西省青年基金项目(No.201601D021080)
中北大学校基金(No.XJJ2016019)
