摘要
为了检测图像清晰的边缘轮廓,对不同边缘检测方法的优缺点进行了分析,提出一种新的基于模糊的边缘检测算法。将梯度幅值和标准差值2个不同的信息源作为模糊系统的输入;模糊系统根据模糊规则和隶属度函数来判断每个像素是否为图像边缘轮廓;使用MatLab 2016开发边缘检测算法集成模拟器,并在不同的场景下进行仿真试验。试验结果表明,基于梯度和标准差的模糊边缘检测方法比其他传统方法具有更好的性能。
In order to detect the clear edge of the image,the pros and cons of different edge detection methods are analyzed,and a new edge detection algorithm based on fuzzy is proposed. Two different information sources,gradient magnitude and standard deviation,are used as inputs to the fuzzy system. The fuzzy system determines whether each pixel is an image edge according to the fuzzy rule and the membership function. Uses MatLab 2016 to develop an edge detection algorithm integrated simulator and performs simulation experiments in different scenarios. The experimental results show that the fuzzy edge detection method based on gradient and standard deviation has better performance than other traditional methods.
作者
曹洪运
赵宇峰
高佳佳
CAO Hong-yun;ZHAO Yu-feng;GAO Jia-jia(School of Computer Science and Engineering,Xi'an Technology University,Xi'an 710021,China;School of Electronic Information Engineering,Xi'an Technology University,Xi'an 710021,China)
出处
《自动化与仪表》
2019年第1期45-49,共5页
Automation & Instrumentation
关键词
边缘检测
模糊逻辑
模糊推理系统
梯度
标准差
edge detection
fuzzy logic
fuzzy decision system
gradient
standard deviation
