基于边缘检测的零件轮廓识别系统开发
|
摘要
针对工业流水线检测中存在的成本大、检测效率低的问题,将轮廓检测技术应用到工业流水线检测中,基于边缘检测方法的基本原理,提出了一种基于边缘检测的零件轮廓识别方法。该方法首先使用Canny边缘检测算法来提取出零件的边缘,并在此基础上进一步提取出零件轮廓的相关特征,最后通过与待检测的零件轮廓特征相比较,从而实现对零件的识别检测;为了验证设计方法的正确性,本文搭建了一套零件轮廓识别系统,并使用工业零件来测试该系统的性能。研究结果表明:该系统能够快速、准确地识别目标零件,满足工业流水线检测的需求。
Aiming at the problems of high cost and low efficiency in industrial pipeline detection,the contour detection technology was applied to industrial pipeline detection. Based on the analysis of the basic principle of edge detection method,a method of part contour recognition based on edge detection was proposed. The method firstly used Canny edge detection algorithm to extract the edge of the part,and then further extracted the related features of the part contour. Finally,by comparing with the contour features of the part to be detected,the recognition and detection of the part can be realized. In order to verify the correctness of the design method,a part contour recognition system was built,and the performance of the system was tested by industrial parts. The results show that the system can quickly and accurately identify the target parts,meet the needs of industrial pipeline inspection.
Aiming at the problems of high cost and low efficiency in industrial pipeline detection,the contour detection technology was applied to industrial pipeline detection. Based on the analysis of the basic principle of edge detection method,a method of part contour recognition based on edge detection was proposed. The method firstly used Canny edge detection algorithm to extract the edge of the part,and then further extracted the related features of the part contour. Finally,by comparing with the contour features of the part to be detected,the recognition and detection of the part can be realized. In order to verify the correctness of the design method,a part contour recognition system was built,and the performance of the system was tested by industrial parts. The results show that the system can quickly and accurately identify the target parts,meet the needs of industrial pipeline inspection.
引文
[1]李晓飞.高速在线机器视觉检测方法的研究[D].天津:天津理工大学控制科学与工程学院,2008.
[2]夏如艇,金飞翔,王昕.基于机器视觉的铁刀检测系统的设计[J].机电工程技术,2017,46(11):63-66,132.
[3]崔淑平.基于Open CV的回转体零件表面缺陷检测研究[D].保定:华北电力大学能源动力与机械工程学院,2015.
[4]许可.基于多特征的图像轮廓检测算法研究[D].西安:长安大学交通运输工程学院,2014.
[5]曾俊.图像边缘检测技术及其应用研究[D].武汉:华中科技大学控制科学与工程学院,2011.
[6]董鸿燕.边缘检测的若干技术研究[D].合肥:国防科学技术大学信息与通信工程学院,2008.
[7]磨少清.边缘检测及其评价方法的研究[D].天津:天津大学检测技术与自动化装置学院,2011.
[8]钟鑫,付俐.一种基于Canny算法的自适应边缘提取方法[J].科学技术与工程,2007,7(16):4067-4069.
[9]王小俊,刘旭敏,关永.基于改进Canny算子的图像边缘检测算法[J].计算机工程,2012,38(14):196-198,202.
[10]陈丹丹.序列图像中手势识别技术研究[D].沈阳:东北大学信息科学与工程学院,2012.
[11]郎瑶.一种改进的Sobel边缘检测算子[J].广西轻工业,2011,27(5):59-60.
[12]张建军,罗静.基于改进Sobel算子的表面裂纹边缘检测算法[J].合肥工业大学学报:自然科学版,2011,34(6):845-847,960.
[13]王冠,丁友东,魏小成.基于改进Sobel算子的文物图像检索[J].计算机技术与发展,2011,21(10):51-54,58.
[14]袁春兰,熊宗龙,周雪花,等.基于Sobel算子的图像边缘检测研究[J].激光与红外,2009,39(1):85-87.
[15]孙增国,韩崇昭.基于Laplacian算子的图像增强[J].计算机应用研究,2007,24(1):222-223,240.
[16]万军,徐汀荣.基于Laplacian算子的图像边缘检测方法研究[J].现代电子技术,2004,27(21):92-93,96.
[17]张彦超.基于边缘和颜色特征的图像检索技术研究[D].武汉:武汉理工大学计算机科学与技术学院,2010.
[18]王雪,李伟,王伟.数字图像处理中边缘检测算子优缺点探讨[J].科技创新导报,2011(16):14-15.
[19]樊娜,李晋惠.图像边缘检测的Prewitt算子的改进算法[J].西安工业学院学报,2005,25(1):37-39,44.
[20]霍冠英,王敏,程晓轩,等.用于侧扫声纳图像边缘检测的改进Canny算子[J].应用科学学报,2011,29(6):613-618.
[21] HANNAT M,ZRIRA N,RAOUI Y,et al. A fast object recognition and categorization technique for robot grasping using the visual bag of words[C]. 2016 5th International Conference on Multimedia Computing and Systems,Marrakech:IEEE,2016.
[22]李光梅,苟岩岩,刘果玲.易拉罐空罐缺陷智能检测气流的设计[J].包装与食品机械,2017(6):33-36.
[23]王晨,庞全.基于轮廓的血细胞图像拼接算法的设计与实现[J].机电工程,2009,26(11):44-47,86.
[2]夏如艇,金飞翔,王昕.基于机器视觉的铁刀检测系统的设计[J].机电工程技术,2017,46(11):63-66,132.
[3]崔淑平.基于Open CV的回转体零件表面缺陷检测研究[D].保定:华北电力大学能源动力与机械工程学院,2015.
[4]许可.基于多特征的图像轮廓检测算法研究[D].西安:长安大学交通运输工程学院,2014.
[5]曾俊.图像边缘检测技术及其应用研究[D].武汉:华中科技大学控制科学与工程学院,2011.
[6]董鸿燕.边缘检测的若干技术研究[D].合肥:国防科学技术大学信息与通信工程学院,2008.
[7]磨少清.边缘检测及其评价方法的研究[D].天津:天津大学检测技术与自动化装置学院,2011.
[8]钟鑫,付俐.一种基于Canny算法的自适应边缘提取方法[J].科学技术与工程,2007,7(16):4067-4069.
[9]王小俊,刘旭敏,关永.基于改进Canny算子的图像边缘检测算法[J].计算机工程,2012,38(14):196-198,202.
[10]陈丹丹.序列图像中手势识别技术研究[D].沈阳:东北大学信息科学与工程学院,2012.
[11]郎瑶.一种改进的Sobel边缘检测算子[J].广西轻工业,2011,27(5):59-60.
[12]张建军,罗静.基于改进Sobel算子的表面裂纹边缘检测算法[J].合肥工业大学学报:自然科学版,2011,34(6):845-847,960.
[13]王冠,丁友东,魏小成.基于改进Sobel算子的文物图像检索[J].计算机技术与发展,2011,21(10):51-54,58.
[14]袁春兰,熊宗龙,周雪花,等.基于Sobel算子的图像边缘检测研究[J].激光与红外,2009,39(1):85-87.
[15]孙增国,韩崇昭.基于Laplacian算子的图像增强[J].计算机应用研究,2007,24(1):222-223,240.
[16]万军,徐汀荣.基于Laplacian算子的图像边缘检测方法研究[J].现代电子技术,2004,27(21):92-93,96.
[17]张彦超.基于边缘和颜色特征的图像检索技术研究[D].武汉:武汉理工大学计算机科学与技术学院,2010.
[18]王雪,李伟,王伟.数字图像处理中边缘检测算子优缺点探讨[J].科技创新导报,2011(16):14-15.
[19]樊娜,李晋惠.图像边缘检测的Prewitt算子的改进算法[J].西安工业学院学报,2005,25(1):37-39,44.
[20]霍冠英,王敏,程晓轩,等.用于侧扫声纳图像边缘检测的改进Canny算子[J].应用科学学报,2011,29(6):613-618.
[21] HANNAT M,ZRIRA N,RAOUI Y,et al. A fast object recognition and categorization technique for robot grasping using the visual bag of words[C]. 2016 5th International Conference on Multimedia Computing and Systems,Marrakech:IEEE,2016.
[22]李光梅,苟岩岩,刘果玲.易拉罐空罐缺陷智能检测气流的设计[J].包装与食品机械,2017(6):33-36.
[23]王晨,庞全.基于轮廓的血细胞图像拼接算法的设计与实现[J].机电工程,2009,26(11):44-47,86.