基于梯度和标准差值的模糊边缘检测
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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.
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.
引文
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[4] Prewitt J M S.Object enhancement and extraction[C]//Picture processing and psychopictorics. Waltham:Academic Press,1970:75-149.
[5] Heath M,Sarkar S,Sanocki T,et al. Comparison of edge detectors:A methodology and initial study[J].Computer Vision&Image Understanding,1998,69(1):38-54.
[6]陈宇云.灰度图像的边缘检测研究[D].成都:电子科技大学,2009.
[7] Marr D,Hildreth E.Theory of edge detection[J].Proceedings of the Royal Society of London,1980,B207(1167):187-217.
[8] Canny J.A computational approach to edge detection[J].IEEE Trans Pattern Anal Machine Intel,1986,8(6):679-697.
[9]许宏科,秦严严,陈会茹.一种基于改进Canny的边缘检测算法[J].红外技术,2014,36(3):210-214.