基于改进的Sobel-Zernike矩法亚像素厚度测量
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摘要
针对Zernike矩亚像素定位算法精度较高,但算法运算时间较长的问题,提出基于Sobel的改进Zernike矩亚像素定位法,该算法通过Sobel检测初步定位护套和绝缘材料的边缘,缩小Zernike矩的计算范围,使得在精度基本不变的情况下,缩短了计算时间,提高了速度;并通过估计边缘点正态分布的均值将轮廓像素宽度缩小在单像素上,提高了算法的精度。通过将该算法与Zernike矩法以及插值法在精度和速度上的对比实验,验证了该算法的优越性,具有应用价值。
In view of the high precision of the Zernike moment subpixel location algorithm,while the algorithm has a long operation time,an improved Zernike moment subpixel location method based on Sobel is proposed in this paper. The algorithm detects the initial location of the sheath and the edge of the insulation material by Sobel,and reduces the computation range of the Zernike moments,so that the computation time is shortened and the speed is increased when the accuracy is basically unchanged. The accuracy of the algorithm is improved by reducing the width of the contour pixel on the single pixel and estimating the mean value of the normal distribution of the edge points. The superiority of the algorithm is verified by comparing the accuracy and speed of the improved Sobel-Zernike moment method,the common Zernike moment method and the improved interpolation method,which has a certain application value.
In view of the high precision of the Zernike moment subpixel location algorithm,while the algorithm has a long operation time,an improved Zernike moment subpixel location method based on Sobel is proposed in this paper. The algorithm detects the initial location of the sheath and the edge of the insulation material by Sobel,and reduces the computation range of the Zernike moments,so that the computation time is shortened and the speed is increased when the accuracy is basically unchanged. The accuracy of the algorithm is improved by reducing the width of the contour pixel on the single pixel and estimating the mean value of the normal distribution of the edge points. The superiority of the algorithm is verified by comparing the accuracy and speed of the improved Sobel-Zernike moment method,the common Zernike moment method and the improved interpolation method,which has a certain application value.
引文
[1] ROSENFELD A,KAK A C. Digital Picture Processing:2nd edn[M].New York:Academic Press,1982.
[2] CANNY J. A Computational Approach to Edge Detection[J]. IEEE Trans Pattern Analysis Mach Intell,1986,8(6):679-698.
[3] HUECKEL MH. An Operator Which Locate Edges in Digitized Pictures[J]. Journal of the Association for Computing Machinery,1971,18(1):113-125.
[4] KRIS J,DIMITRIS A. Subpixel Edge Localization and the Interpolation of Still Images[J]. IEEE Trans on Image Processing,1995,4(3):285-295.
[5] GHOSAL S,MEHROTRA R. Orthogonal Moment Operators for Subpixel Edge Detection[J]. Pattern Recognition,1993,26(2):295-306.
[6] GB/T 2951. 11-2008.电缆绝缘和护套材料通用试验方法[P].
[7]王吉林,姚励,赵力.基于改进的多项式插值亚像素法电缆护套材料厚度测量[J].电测与仪表,2009,46(12):25-28.Wang Jilin,Yao Li,Zhao Li. Polynomial interpolation based on an improved sub-pixel method of thickness measurement of cable sheath material[J]. Electrical Measurement&Instrumentation,2009,46(12):25-28.
[8]李忠海,金海洋,邢晓红.整数阶滤波的分数阶Sobel算子的边缘检测算法[J].计算机工程与应用,2018,54(4):179-184.Li Zhonghai,Jin Haiyang,Xing Xiaohong. Edge detection algorithm of fractional order sobel operator for integer order differential filtering[J].Computer Engineering and Applications,2018,54(4):179-184.
[9] Ta Yang Goh,Shafriza Nisha Basah,Haniza Yazid. Performance analysis of image thresholding:Otsu technique[J]. Measurement,2018,1(114):298-307.
[10]张帆,陈相廷,张新红. DSA影像血管狭窄的亚像素级自动检测算法[J].激光与光电子学进展,2018,55(4):41101.Zhang Fan,Chen Xiangting,Zhang Xinhong. Subpixel Stenosis Automatic Detection of DSA Blood Vessel[J]. Laser&Optoelectronics Progress,2018,55(4):41101.
[11]刘大千,刘万军,费博雯.先验模型约束的抗干扰轮廓跟踪[J].中国图象图形学报,2017,22(4):502-515.Liu Daqian,Liu Wanjun,Fei Bowen. Anti-interference contour tracking under prior model constraint[J]. Journal of Image and Graphics,2017,22(4):502-515.
[12]周锋,卞金洪,赵力.基于图像亚像素处理的电缆护套厚度精确测量[J].电测与仪表,2011,48(10):14-18.Zhou Feng,Bian Jinhong,Zhao Li. Measurement of Cable Thickness Based on Sub-pixel Image Processing[J]. Electrical Measurement&Instrumentation,2011,48(10):14-18.
[13]沈舷,周锋,赵力.基于局部区域灰度亚像素法电缆护套厚度精确测量[J].电测与仪表,2016,53(8):62-68.Shen Xian,Zhou Feng,Zhao Li. A sub-pixel edge detection algorithm based on local area gray-scale of thickness measurement of cable sheath material[J]. Electrical Measurement&Instrumentation,2016,53(8):62-68.
[2] CANNY J. A Computational Approach to Edge Detection[J]. IEEE Trans Pattern Analysis Mach Intell,1986,8(6):679-698.
[3] HUECKEL MH. An Operator Which Locate Edges in Digitized Pictures[J]. Journal of the Association for Computing Machinery,1971,18(1):113-125.
[4] KRIS J,DIMITRIS A. Subpixel Edge Localization and the Interpolation of Still Images[J]. IEEE Trans on Image Processing,1995,4(3):285-295.
[5] GHOSAL S,MEHROTRA R. Orthogonal Moment Operators for Subpixel Edge Detection[J]. Pattern Recognition,1993,26(2):295-306.
[6] GB/T 2951. 11-2008.电缆绝缘和护套材料通用试验方法[P].
[7]王吉林,姚励,赵力.基于改进的多项式插值亚像素法电缆护套材料厚度测量[J].电测与仪表,2009,46(12):25-28.Wang Jilin,Yao Li,Zhao Li. Polynomial interpolation based on an improved sub-pixel method of thickness measurement of cable sheath material[J]. Electrical Measurement&Instrumentation,2009,46(12):25-28.
[8]李忠海,金海洋,邢晓红.整数阶滤波的分数阶Sobel算子的边缘检测算法[J].计算机工程与应用,2018,54(4):179-184.Li Zhonghai,Jin Haiyang,Xing Xiaohong. Edge detection algorithm of fractional order sobel operator for integer order differential filtering[J].Computer Engineering and Applications,2018,54(4):179-184.
[9] Ta Yang Goh,Shafriza Nisha Basah,Haniza Yazid. Performance analysis of image thresholding:Otsu technique[J]. Measurement,2018,1(114):298-307.
[10]张帆,陈相廷,张新红. DSA影像血管狭窄的亚像素级自动检测算法[J].激光与光电子学进展,2018,55(4):41101.Zhang Fan,Chen Xiangting,Zhang Xinhong. Subpixel Stenosis Automatic Detection of DSA Blood Vessel[J]. Laser&Optoelectronics Progress,2018,55(4):41101.
[11]刘大千,刘万军,费博雯.先验模型约束的抗干扰轮廓跟踪[J].中国图象图形学报,2017,22(4):502-515.Liu Daqian,Liu Wanjun,Fei Bowen. Anti-interference contour tracking under prior model constraint[J]. Journal of Image and Graphics,2017,22(4):502-515.
[12]周锋,卞金洪,赵力.基于图像亚像素处理的电缆护套厚度精确测量[J].电测与仪表,2011,48(10):14-18.Zhou Feng,Bian Jinhong,Zhao Li. Measurement of Cable Thickness Based on Sub-pixel Image Processing[J]. Electrical Measurement&Instrumentation,2011,48(10):14-18.
[13]沈舷,周锋,赵力.基于局部区域灰度亚像素法电缆护套厚度精确测量[J].电测与仪表,2016,53(8):62-68.Shen Xian,Zhou Feng,Zhao Li. A sub-pixel edge detection algorithm based on local area gray-scale of thickness measurement of cable sheath material[J]. Electrical Measurement&Instrumentation,2016,53(8):62-68.