墙体浅层裂缝检测的数字化图像处理方法
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摘要
数字图像处理技术应用于墙体浅层裂缝测量可获取数字化的裂缝信息,具有操作灵活、测量精度高等优点,可以克服传统墙体裂缝宽度测量技术的费时费力、精度不高等不足,具有广泛的应用前景。该文提出了一种新的基于神经网络进行图像分割的方法,对墙体裂缝图像进行提取,一定程度上克服了传统分割方法对背景图像的依赖性,减少了伪点和伪区域,降低了采用形态学算法带来的不准确性,提高了测量准确性;同时介绍了对墙体裂缝图像进行数字化处理的具体方法和流程。结合工程实例进行实验,结果表明该技术测量精确,操作方便,具有明显的工程意义和一定的实用价值。
A new method of image segmentation based on neural network was proposed to extract the cracks image,with which it could overcome,in some extent,the dependence of the background image and reduce the pseudo-points and pseudo-regions.The measurement accuracy can be improved compared with that from morphological algorithm.Furthermore,the specific methods and processes to measure the walls crack with image digital processing were presented.And with the case study,it was found that this method can measure the cracks accurately with convenient operation.
A new method of image segmentation based on neural network was proposed to extract the cracks image,with which it could overcome,in some extent,the dependence of the background image and reduce the pseudo-points and pseudo-regions.The measurement accuracy can be improved compared with that from morphological algorithm.Furthermore,the specific methods and processes to measure the walls crack with image digital processing were presented.And with the case study,it was found that this method can measure the cracks accurately with convenient operation.
引文
[1]于飞,赵国兴,郑国泰,等.框架填充墙裂缝调查与成因分析[J].新型建筑材料:2006(1):8-9.
[2]AMMOUCHE A,RISS J,BREYSSE D,et a1.Imageanalysis for the automated study of microcracks inconcrete[J].Cement and Concrete Composites,2001,23:267-278.
[3]查旭东,王文强.基于图像处理技术的连续配筋混凝土路面裂缝宽度检测方法[J].长沙理工大学学报(自然科学版),2007,4(1):13-17.
[4]王静,李鸿琦,等.数字图像相关方法在桥梁裂缝变形监测中的应用[J].力学季刊,2003,24(4):512-516.
[5]耿飞,解建光,等.图像分析技术对混凝土裂缝的定量评价[J].混凝土,2005,187(5):79-87.
[6]王雷,黄战华,蔡怀宇,等.工程结构构件裂缝图像的处理与宽度测量[J].计算机测量与控制,2006,14(8):992-1003.
[7]DESHMUKH S,SHINDE N.An adaptive color imagesegmentation[J].Electronic Letters on ComputerVision and Image Analysis,2005,5:12-23.
[8]CHENG H,JIANG X,SUN Y,et al.Color imagesegmentation:advances and prospects[J].PatternRecognition,2001,34(12):2259-2281.
[9]WANG Y,WANG Y,LIU F,et al.The segmentationof optic cup in eye funds image based on neural network[J].Journal of Basic Science And Engineering,Chinese,1998,6:314-318.
[10]CELIK T,DEMIREL H.Fire detection in videosequences using a generic color model[J].Fire SafetyJournal,2009,44:147-158.
[11]KERMANI B,SCHIFFMAN S,NAGLE H.Performance of the Levenberg-Marquardt neuralnetwork training method in electronic nose applications[J].Sensors and Actuators B:Chemical,2005,110:13-22.
[12]NOR A,SUBHI M,KAMAL Z,et al.Suitablefeatures selection for the HMLP and MLP networks toidentify the shape of aggregate[J].Construction andBuilding Materials.2008,22(3):402-410.
[13]Bishop C M.Neural networks for pattern recognition[M].Oxford:Oxford University Press,2004.
[14]日本混凝土工程协会.混凝土裂缝调查及修补规程[M].北京:地震出版社,1992.
[15]梁建国,方亮,等.美国砌体结构房屋墙体裂缝的控制[J].建筑砌块与砌块建筑,2007(6):2-6.
[2]AMMOUCHE A,RISS J,BREYSSE D,et a1.Imageanalysis for the automated study of microcracks inconcrete[J].Cement and Concrete Composites,2001,23:267-278.
[3]查旭东,王文强.基于图像处理技术的连续配筋混凝土路面裂缝宽度检测方法[J].长沙理工大学学报(自然科学版),2007,4(1):13-17.
[4]王静,李鸿琦,等.数字图像相关方法在桥梁裂缝变形监测中的应用[J].力学季刊,2003,24(4):512-516.
[5]耿飞,解建光,等.图像分析技术对混凝土裂缝的定量评价[J].混凝土,2005,187(5):79-87.
[6]王雷,黄战华,蔡怀宇,等.工程结构构件裂缝图像的处理与宽度测量[J].计算机测量与控制,2006,14(8):992-1003.
[7]DESHMUKH S,SHINDE N.An adaptive color imagesegmentation[J].Electronic Letters on ComputerVision and Image Analysis,2005,5:12-23.
[8]CHENG H,JIANG X,SUN Y,et al.Color imagesegmentation:advances and prospects[J].PatternRecognition,2001,34(12):2259-2281.
[9]WANG Y,WANG Y,LIU F,et al.The segmentationof optic cup in eye funds image based on neural network[J].Journal of Basic Science And Engineering,Chinese,1998,6:314-318.
[10]CELIK T,DEMIREL H.Fire detection in videosequences using a generic color model[J].Fire SafetyJournal,2009,44:147-158.
[11]KERMANI B,SCHIFFMAN S,NAGLE H.Performance of the Levenberg-Marquardt neuralnetwork training method in electronic nose applications[J].Sensors and Actuators B:Chemical,2005,110:13-22.
[12]NOR A,SUBHI M,KAMAL Z,et al.Suitablefeatures selection for the HMLP and MLP networks toidentify the shape of aggregate[J].Construction andBuilding Materials.2008,22(3):402-410.
[13]Bishop C M.Neural networks for pattern recognition[M].Oxford:Oxford University Press,2004.
[14]日本混凝土工程协会.混凝土裂缝调查及修补规程[M].北京:地震出版社,1992.
[15]梁建国,方亮,等.美国砌体结构房屋墙体裂缝的控制[J].建筑砌块与砌块建筑,2007(6):2-6.
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