基于数学形态学和CCD的非接触实时测量及算法研究
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摘要
火炮静态参数检测是火炮定型试验中评定火炮性能的重要依据之一,其中火炮身管弯曲度和缠角的测量是火炮定型试验中必不可少的主要检测项目。目前静态参数测量所采用的设备普遍存在着测量口径范围较小的局限,而且测量精度低,难以满足当前兵器试验基地火炮测量的要求。
为克服上述测量设备和测量方法的局限性,满足靶场火炮检测的需求,本论文基于数学形态学和CCD的非接触测量,结合边缘检测和定位技术,并本着实用、可靠、先进、经济与操作方便相结合的原则,提出一种高性能的光机电一体化的火炮静态参数实时测量系统。
该系统所涉及的数字图像测量是近年来基于光学测量原理形成的一种新型测量技术,它以光学为基础,融合电子学、计算机技术、激光技术、图像处理技术等现代科学技术为一体,组成光、电、计算机综合的测量技术,被广泛应用于几何量的尺寸测量、航空遥感测量、高精度定位、精密复杂零件的微尺寸测量和外观检测等与图像有关的技术领域中。边缘检测及定位技术在图像工程中占有重要的地位和作用,所以对边缘检测与精确定位的研究一直是图像技术研究中的热点和焦点。本论文在经典定位技术的基础上,提出了基于人眼视觉的边缘定位技术,并将其应用在火炮内膛图像的检测上。
数学形态学由于在诸多领域中成功的应用,使其成为一门发展非常迅速的新兴图像分析学科。本论文将数学形态学的基本原理和方法应用于火炮身管测量中,取得了良好的测量效果。
The static parameter measurement of cannons is one of the important performance evidences in the cannon finalizing test, in which, the measurement of cannon barrel straightness and twist pitch of rifling is the primary test program. At present, most equipments for the measurement are not satisfied with the current needs of weapon test base for the limit of small caliber scale and low precision.
In order to overcome the above shortcomings and fit the test for cannon, in this thesis, we present a real-time measurement system for cannon static parameter based on mathematical morphology and CCD non-connect measurement and edge location, which is reliable, advanced, economical and operation convenient.
Digital image measurement used by the system is a novel measuring technique. It is based on the optics and composed of optics, electronics and computers. It syncretizes electronics, computer science, laser science, and image processing technology. It is used widely in the fields such as geometry dimension measurement, aviation remote sensing measurement, high precision locating and face location about image. Edge location is always the focus in the image measurement for the important status and effect in the projects. In this thesis, edge location based on human vision is presented and applied to the measurement of cannon bore image.
Mathematical morphology has been also developed quickly for its successful application in many fields. In the cannon barrel measurement, it achieves prospective effect when used the theory and methods of mathematical morphology.
为克服上述测量设备和测量方法的局限性,满足靶场火炮检测的需求,本论文基于数学形态学和CCD的非接触测量,结合边缘检测和定位技术,并本着实用、可靠、先进、经济与操作方便相结合的原则,提出一种高性能的光机电一体化的火炮静态参数实时测量系统。
该系统所涉及的数字图像测量是近年来基于光学测量原理形成的一种新型测量技术,它以光学为基础,融合电子学、计算机技术、激光技术、图像处理技术等现代科学技术为一体,组成光、电、计算机综合的测量技术,被广泛应用于几何量的尺寸测量、航空遥感测量、高精度定位、精密复杂零件的微尺寸测量和外观检测等与图像有关的技术领域中。边缘检测及定位技术在图像工程中占有重要的地位和作用,所以对边缘检测与精确定位的研究一直是图像技术研究中的热点和焦点。本论文在经典定位技术的基础上,提出了基于人眼视觉的边缘定位技术,并将其应用在火炮内膛图像的检测上。
数学形态学由于在诸多领域中成功的应用,使其成为一门发展非常迅速的新兴图像分析学科。本论文将数学形态学的基本原理和方法应用于火炮身管测量中,取得了良好的测量效果。
The static parameter measurement of cannons is one of the important performance evidences in the cannon finalizing test, in which, the measurement of cannon barrel straightness and twist pitch of rifling is the primary test program. At present, most equipments for the measurement are not satisfied with the current needs of weapon test base for the limit of small caliber scale and low precision.
In order to overcome the above shortcomings and fit the test for cannon, in this thesis, we present a real-time measurement system for cannon static parameter based on mathematical morphology and CCD non-connect measurement and edge location, which is reliable, advanced, economical and operation convenient.
Digital image measurement used by the system is a novel measuring technique. It is based on the optics and composed of optics, electronics and computers. It syncretizes electronics, computer science, laser science, and image processing technology. It is used widely in the fields such as geometry dimension measurement, aviation remote sensing measurement, high precision locating and face location about image. Edge location is always the focus in the image measurement for the important status and effect in the projects. In this thesis, edge location based on human vision is presented and applied to the measurement of cannon bore image.
Mathematical morphology has been also developed quickly for its successful application in many fields. In the cannon barrel measurement, it achieves prospective effect when used the theory and methods of mathematical morphology.
引文
[1]章毓晋.图像处理和分析.北京：清华大学出版社,2000.
[2]崔屹.图像处理与分析-数学形态学方法及应用.北京：科学出版社.2002.
[3]于起峰,陆宏伟,刘肖琳.基于图像的精密测量与运动测量.科学出版社,2002.
[4]王庆有.CCD应用技术.天津大学出版社.2000.
[5]大恒图像系列产品.
[6]钟志光,卢君,刘伟荣,visual c++.net数字图像处理实例与解析,北京,清华大学出版社.
[7]X. J. Deng, R. S. Yun et al.,“A new edge detection operator—sine operator”, Electron and informatics Trans.24(11):1462-1469,2002
[8]R. M. Haralick,“Digital step edges from zero crossing of second direction derivatives”. IEEE Trans. Pattern Anal. AndMachine Intell., PAMⅡ-6(1):58-68, 1984.
[9]T.O. Binford,“Inferring surfaces from images”. Artfical Intell.,17(8):205-244, 1981.
[10]V. S. Nalwa, T.O.Binford,“On detecting edges”. IEEE Trans. Pattern Anal. And Machine Intell., PAMII-8(6):699～714,1986.
[11]V. Torre, T.A.Poggio,“On egde detection”. IEEE Trans. Pattern Anal. And Machine Intell., PAMII-8(2):147～163,1986.
[12]M. A. Fischler, J.M.Tenenbaum, H.C. Wolf,“Detection of roads and linear structures in low resolution aerial imagery”. CVGIP:Computer Graphics and Image Processing. 11(3):201-223,1981.
[13]J. S. Chen. Detection,“Detection, localization, and estimation of edges”. IEEE Trans. PAMII,11(2):191-198,1989.
[14]G. Z. Hu, X. P. Cao,“Subpixel edge detector using expection of first-order derivatives”. SPIE,1657:415-425,1992
[15]M. F. Hueckel,“A local visual operator which recognizes edges and lines”. JACM, 20:634-647,1973.
[16]A. M. Tahmasebi, and S. Kasaei,“A novel adaptive approach to fingerprint enhancement”. Signal Processing:Image Communication 17(10):849-855,2002
[17]A. J. Tabatabai, O. R. Mitchell,“Edge location to subpixel values in digitial
imagery”. IEEE Trans. Pattern Anal.Machine Intell., PAMI-6(2):188-201,1984.
[18]A. Huertas, G. Medioni,“Detection of intensity changes with subpixel accuracy using Laplacian-Gaussian masks”. IEEE Trans. Pattern Anal. Machine Intell, PAMI-8(5):651-664,1986
[19]A. Englander,“Expanding machine vision gauging with subpixel techniques”. Sensors-J:Machine Perception,4(6):9-18,1987.
[20]E. P. Lyver,O. R. Mitchell,“Subpixel measurements using a moment—based on edge operator”. IEEE Trans. Pattern Anal. Machine Intell,11(12):1293-1308, 1989.
[21]Y. J. Zhang, Z. Fu,“Subpixel edge detection using the information of the tangential direction”. Pattern recognition and artificial intelligence.10(1):83-88, 1997.
[22]H. S. Liu, and L. Q. Hung,“A medical image processing method based on human eye visual property”. Opto-Electronic Engineering:28(4),38-41,2001
[23]Q.B. BAI and ZH. F. HAN,“Automatic Detection of Cannon's Chamber Based on CCD Imaging and Computer Image Processing Technique”, Computer Measurement & Control:10(2),124-126,2002.
[24]G.Q. HUANG and J.G HUANG,“Three dimensional CCD photoelectric measurement system and it's application”, SPIE (3173):370-374.
[25]L. Y. HE and J. ZH. DAI,“A Subdivision Method for the High Precision Image Measurement System”, Opto-Electronic Engineering:26,111-115,1999.
[26]J.L. Li and G..Q. Ding“Method for improving precision in non-contact measurement by linear CCD”, Optics and Precision Engineering:10 (6):282-286, 2002.
[27]R. M.. Haralick,“Digital step edges from zero crossing of second direction derivatives”, IEEE Trans. Pattern Anal. Machine Intell., PAMⅡ-6(1):58-68,1984.
[28]Y. J. Zhang and Z. Fu,“Subpixel edge detection using the information of the tangential direction”, Pattern Recognition and Artificial Intelligence,10(1):83-88, 1997.
[29]E. P. Lyver and O. R. Mitchell,“Subpixel measurements using a moment—based on edge operator”, IEEE Trans. Pattern Anal. Machine Intell.,11(12):1293-1308, 1989.
[30]A. Englander,“Expanding machine vision gauging with subpixel techniques” Sensors-J:Machine Perception,4(6):9-18,1987.
[31]Amit C, Lawrence HS, James SD,“Deformable boundary finding in medical images by integrating gradient and region information”, IEEE Trans Med Imaging, 15(6):859-870,1996.
[32]Kass M, Witkin A, Terzopouls D.Snake:“Active Contour Models”, Proceedings-First International Conference on Computer Vision,259-268,1988.
[33]Otsu N,“Threshold Selection Method from Gray-level Histograms”, IEEE Trans. Syst., Man, Cybernetics, SMC-9(1):62-66,1979.
[34]P.Y.Yin,“A Fast Scheme for Optimal Thresholding Using Genetic Algorithms”, Signal Processing,72(2):85-95,1999.
[35]高春明,二值图像骨架的数学形态学描述及重建,长沙铁道学院学报,14(4)：89-93,1996。
[36]季立江,廖俊必,史伟,基于图像处理的炮管轴线直线度检测方法,自动检测技术,21(6)：29-32,2002。
[37]刘恒殊,黄廉卿,基于人眼视觉特性的医学图像处理方法,光电工程,28(4)：38-41,2001。
[38]白庆本,韩兆福,基于CCD成像和计算机图像处理技术的火炮内膛自动检测,计算机测量与控制,10(2)：2002。
[39]莫剑英,PSD在身管弯曲度测量中的应用,华北工学院学报,16(3)：202-206,1995。
[40]贺安之,吕爱民,火炮身管弯曲度、炮口角检测系统的研究,弹道学报,9(3)：59-62,1997。
[41]邵思杰,李建中,火炮药室参数测量技术的研究,弹道学报,10(4)：88-91,1998。
[42]吕爱民,袁红星,身管弯曲度测量方法的研究,南京理工大学学报,20(5)：477-480,1996。
[43]马永军,方廷,火炮身管内膛直线度自动检测系统,仪表技术,1：11-12-2002。
[2]崔屹.图像处理与分析-数学形态学方法及应用.北京：科学出版社.2002.
[3]于起峰,陆宏伟,刘肖琳.基于图像的精密测量与运动测量.科学出版社,2002.
[4]王庆有.CCD应用技术.天津大学出版社.2000.
[5]大恒图像系列产品.
[6]钟志光,卢君,刘伟荣,visual c++.net数字图像处理实例与解析,北京,清华大学出版社.
[7]X. J. Deng, R. S. Yun et al.,“A new edge detection operator—sine operator”, Electron and informatics Trans.24(11):1462-1469,2002
[8]R. M. Haralick,“Digital step edges from zero crossing of second direction derivatives”. IEEE Trans. Pattern Anal. AndMachine Intell., PAMⅡ-6(1):58-68, 1984.
[9]T.O. Binford,“Inferring surfaces from images”. Artfical Intell.,17(8):205-244, 1981.
[10]V. S. Nalwa, T.O.Binford,“On detecting edges”. IEEE Trans. Pattern Anal. And Machine Intell., PAMII-8(6):699～714,1986.
[11]V. Torre, T.A.Poggio,“On egde detection”. IEEE Trans. Pattern Anal. And Machine Intell., PAMII-8(2):147～163,1986.
[12]M. A. Fischler, J.M.Tenenbaum, H.C. Wolf,“Detection of roads and linear structures in low resolution aerial imagery”. CVGIP:Computer Graphics and Image Processing. 11(3):201-223,1981.
[13]J. S. Chen. Detection,“Detection, localization, and estimation of edges”. IEEE Trans. PAMII,11(2):191-198,1989.
[14]G. Z. Hu, X. P. Cao,“Subpixel edge detector using expection of first-order derivatives”. SPIE,1657:415-425,1992
[15]M. F. Hueckel,“A local visual operator which recognizes edges and lines”. JACM, 20:634-647,1973.
[16]A. M. Tahmasebi, and S. Kasaei,“A novel adaptive approach to fingerprint enhancement”. Signal Processing:Image Communication 17(10):849-855,2002
[17]A. J. Tabatabai, O. R. Mitchell,“Edge location to subpixel values in digitial
imagery”. IEEE Trans. Pattern Anal.Machine Intell., PAMI-6(2):188-201,1984.
[18]A. Huertas, G. Medioni,“Detection of intensity changes with subpixel accuracy using Laplacian-Gaussian masks”. IEEE Trans. Pattern Anal. Machine Intell, PAMI-8(5):651-664,1986
[19]A. Englander,“Expanding machine vision gauging with subpixel techniques”. Sensors-J:Machine Perception,4(6):9-18,1987.
[20]E. P. Lyver,O. R. Mitchell,“Subpixel measurements using a moment—based on edge operator”. IEEE Trans. Pattern Anal. Machine Intell,11(12):1293-1308, 1989.
[21]Y. J. Zhang, Z. Fu,“Subpixel edge detection using the information of the tangential direction”. Pattern recognition and artificial intelligence.10(1):83-88, 1997.
[22]H. S. Liu, and L. Q. Hung,“A medical image processing method based on human eye visual property”. Opto-Electronic Engineering:28(4),38-41,2001
[23]Q.B. BAI and ZH. F. HAN,“Automatic Detection of Cannon's Chamber Based on CCD Imaging and Computer Image Processing Technique”, Computer Measurement & Control:10(2),124-126,2002.
[24]G.Q. HUANG and J.G HUANG,“Three dimensional CCD photoelectric measurement system and it's application”, SPIE (3173):370-374.
[25]L. Y. HE and J. ZH. DAI,“A Subdivision Method for the High Precision Image Measurement System”, Opto-Electronic Engineering:26,111-115,1999.
[26]J.L. Li and G..Q. Ding“Method for improving precision in non-contact measurement by linear CCD”, Optics and Precision Engineering:10 (6):282-286, 2002.
[27]R. M.. Haralick,“Digital step edges from zero crossing of second direction derivatives”, IEEE Trans. Pattern Anal. Machine Intell., PAMⅡ-6(1):58-68,1984.
[28]Y. J. Zhang and Z. Fu,“Subpixel edge detection using the information of the tangential direction”, Pattern Recognition and Artificial Intelligence,10(1):83-88, 1997.
[29]E. P. Lyver and O. R. Mitchell,“Subpixel measurements using a moment—based on edge operator”, IEEE Trans. Pattern Anal. Machine Intell.,11(12):1293-1308, 1989.
[30]A. Englander,“Expanding machine vision gauging with subpixel techniques” Sensors-J:Machine Perception,4(6):9-18,1987.
[31]Amit C, Lawrence HS, James SD,“Deformable boundary finding in medical images by integrating gradient and region information”, IEEE Trans Med Imaging, 15(6):859-870,1996.
[32]Kass M, Witkin A, Terzopouls D.Snake:“Active Contour Models”, Proceedings-First International Conference on Computer Vision,259-268,1988.
[33]Otsu N,“Threshold Selection Method from Gray-level Histograms”, IEEE Trans. Syst., Man, Cybernetics, SMC-9(1):62-66,1979.
[34]P.Y.Yin,“A Fast Scheme for Optimal Thresholding Using Genetic Algorithms”, Signal Processing,72(2):85-95,1999.
[35]高春明,二值图像骨架的数学形态学描述及重建,长沙铁道学院学报,14(4)：89-93,1996。
[36]季立江,廖俊必,史伟,基于图像处理的炮管轴线直线度检测方法,自动检测技术,21(6)：29-32,2002。
[37]刘恒殊,黄廉卿,基于人眼视觉特性的医学图像处理方法,光电工程,28(4)：38-41,2001。
[38]白庆本,韩兆福,基于CCD成像和计算机图像处理技术的火炮内膛自动检测,计算机测量与控制,10(2)：2002。
[39]莫剑英,PSD在身管弯曲度测量中的应用,华北工学院学报,16(3)：202-206,1995。
[40]贺安之,吕爱民,火炮身管弯曲度、炮口角检测系统的研究,弹道学报,9(3)：59-62,1997。
[41]邵思杰,李建中,火炮药室参数测量技术的研究,弹道学报,10(4)：88-91,1998。
[42]吕爱民,袁红星,身管弯曲度测量方法的研究,南京理工大学学报,20(5)：477-480,1996。
[43]马永军,方廷,火炮身管内膛直线度自动检测系统,仪表技术,1：11-12-2002。