基于色彩特征与邻域信息的焊点定位方法
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摘要
为防止集成电路由于元件相互影响及受到外部干扰而无法正常工作,对高集成度电路板进行绝缘封装必不可少.针对印刷电路板(printed circuit board,PCB)上焊点区域小、数量多、位置密集、形态多样等问题,提出基于色彩特征与邻域信息的多形态焊点定位方法.首先通过建立色彩特征模型,提取PCB的单色色度区间特征与多色色差特征;然后提出了基于色彩特征的多形态焊点定位方法,在完成焊点初定位的基础上,采用窗口扫描法提取像素点的邻域信息,进一步提出基于邻域信息的焊点精确定位优化方法,能够有效地提高PCB焊点区域的定位精度.实验结果表明,该方法能大幅提高焊点区域的填充率及滤除误判像素点,满足对PCB上多形态焊点区域的精确定位需求.
In order to prevent the integrated circuit from inter-inference or external interference of the components, it is necessary to keep the high integration circuit board in the insulated encapsulation. Considering the current Printed Circuit Board(PCB) requires small welding, large quantity, intensive distribution, varied shapes, a color feature and neighborhood information based method is proposed in this paper. A color feature model is first established to extract the features of chromaticity interval and color difference. Afterwards, the multi-shaped solder joints location method based on the color feature is proposed to determine the location of the solder joints. On the basis of solder joint positioning, the window scanning is used to extract the neighborhood information of pixel points. The solder joint location is further optimized based on the neighborhood information, where the positioning accuracy of the PCB solder joint area is improved effectively. It is shown from the test results that the precise positioning requirements of the multi-pattern solder joint area on the PCB could be fulfilled as the proposed method could effectively improve the filling rate of the solder joint areas yet reduce numbers of the misplaced pixel points.
In order to prevent the integrated circuit from inter-inference or external interference of the components, it is necessary to keep the high integration circuit board in the insulated encapsulation. Considering the current Printed Circuit Board(PCB) requires small welding, large quantity, intensive distribution, varied shapes, a color feature and neighborhood information based method is proposed in this paper. A color feature model is first established to extract the features of chromaticity interval and color difference. Afterwards, the multi-shaped solder joints location method based on the color feature is proposed to determine the location of the solder joints. On the basis of solder joint positioning, the window scanning is used to extract the neighborhood information of pixel points. The solder joint location is further optimized based on the neighborhood information, where the positioning accuracy of the PCB solder joint area is improved effectively. It is shown from the test results that the precise positioning requirements of the multi-pattern solder joint area on the PCB could be fulfilled as the proposed method could effectively improve the filling rate of the solder joint areas yet reduce numbers of the misplaced pixel points.
引文
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[13]Qin Xujia,Wang Huiling,Du Yicheng,et al.Structured light image enhancement algorithm based on Retinex in HSV color space[J].Journal of Computer-Aided Design&Computer Graphics,2013,25(4):487-493(in Chinese)(秦绪佳,王慧玲,杜轶诚,等.HSV色彩空间的Retinex结构光图像增强算法[J].计算机辅助设计与图形学学报,2013,25(4):487-493)
[14]Taguchi A,Hoshi Y.Color image enhancement in HSI color space without gamut problem[J]IEICE Transactions on Fundamentals of Electronics,Communications and Computer Sciences,2015,e98(2):792-795
[15]Palsokar A,Warnekar C S.A RGB-HSI conversion based model to map the colour perception into audio equivalent to assist visually impaired persons[C]//Proceedings of IEEE the 6th International Conference on Advanced Computing.Washington D C:IEEE Computer Society Press,2016:484-487
[16]Huang Bin,Sun Yongrong,Yang Bowen,et al.Drogue image detecting and tracking based on iterative least squares ellipse fitting[J].Journal of Image and Graphics,2014,19(8):1202-1209(in Chinese)(黄斌,孙永荣,杨博文,等.迭代最小二乘椭圆拟合的锥套图像检测与跟踪[J].中国图象图形学报,2014,19(8):1202-1209)
[2]Xie Hongwei,Zhang Xianmin,Kuang Yongcong.Solder joint inspection method based on image feature statistical analysis[J]Chinese Journal of Scientific Instrument,2011,32(2):401-407(in Chinese)(谢宏威,张宪民,邝泳聪.基于图像特征统计分析的PCB焊点检测方法[J].仪器仪表学报,2011,32(2):401-407)
[3]Xiang F P,Li E P,Wei X C,et al.A particle swarm optimization-based approach for predicting maximum radiated emission from PCBs with dominant radiators[J].IEEE Transactions on Electromagnetic Compatibility,2015,57(5):1197-1205
[4]Said A F,Bennett B L,Karam L J,et al.Automated detection and classification of non-wet solder joints[J].IEEE Transactions on Automation Science and Engineering,2010,8(1):67-80
[5]Wu H,Zhang X M,Xie H W,et al.Classification of solder joint using feature selection based on bayes and support vector machine[J].IEEE Transactions on Components,Packaging and Manufacturing Technology,2013,3(3):516-522
[6]Wu Fupei,Zhang Xianmin,Kuang Yongcong,et al.Robust positioning algorithm of lead-free solder joints based on graylevel integration projection[J].Journal of South China University of Technology:Natural Science Edition,2009,37(9):98-102+116(in Chinese)(吴福培,张宪民,邝泳聪,等.无铅焊点鲁棒定位的灰度积分投影算法[J].华南理工大学学报:自然科学版,2009,37(9):98-102+116)
[7]Han K,Wang X,Yu C L.An efficient visual tracking method based on single CCD camera[C]//Proceedings of the International Conference on Machine Learning and Cybernetics.Washington D C:IEEE Computer Society Press,2012,3:1163-1168
[8]Liu J C,Fan Z,Olsen S I,et al.Boosting active contours for weld pool visual tracking in automatic arc welding[J].IEEE Transactions on Automation Science and Engineering,2017,14(2):1096-1108
[9]Wang Z Z.An imaging and measurement system for robust reconstruction of weld pool during arc welding[J].IEEE Transactions on Industrial Electronics,2015,62(8):5109-5118
[10]Xie Hongwei,Zhang Kun,Kuang Yongcong,et al.Intelligent positioning algorithm of solder joints based on color features[J].Journal of South China University of Technology:Natural Science Edition,2013,41(3):116-121+128(in Chinese)(谢宏威,张坤,邝泳聪,等.基于颜色特征的智能焊点定位算法[J].华南理工大学学报:自然科学版,2013,41(3):116-121+128)
[11]Khan J F,Bhuiyan S M A,Adhami R R.Image segmentation and shape analysis for road-sign detection[J].IEEE Transactions on Intelligent Transportation Systems.2011,12(1):83-96
[12]Gonzalez R C,Woods R E.Digital image processing[M].3rd ed.Beijing:Publishing House of Electronics Industry,2011:72-80(in Chinese)(Gonzalez R C,Woods R E.数字图像处理[M].阮秋琦,阮宇智,等译.3版.北京:电子工业出版社,2011:72-80)
[13]Qin Xujia,Wang Huiling,Du Yicheng,et al.Structured light image enhancement algorithm based on Retinex in HSV color space[J].Journal of Computer-Aided Design&Computer Graphics,2013,25(4):487-493(in Chinese)(秦绪佳,王慧玲,杜轶诚,等.HSV色彩空间的Retinex结构光图像增强算法[J].计算机辅助设计与图形学学报,2013,25(4):487-493)
[14]Taguchi A,Hoshi Y.Color image enhancement in HSI color space without gamut problem[J]IEICE Transactions on Fundamentals of Electronics,Communications and Computer Sciences,2015,e98(2):792-795
[15]Palsokar A,Warnekar C S.A RGB-HSI conversion based model to map the colour perception into audio equivalent to assist visually impaired persons[C]//Proceedings of IEEE the 6th International Conference on Advanced Computing.Washington D C:IEEE Computer Society Press,2016:484-487
[16]Huang Bin,Sun Yongrong,Yang Bowen,et al.Drogue image detecting and tracking based on iterative least squares ellipse fitting[J].Journal of Image and Graphics,2014,19(8):1202-1209(in Chinese)(黄斌,孙永荣,杨博文,等.迭代最小二乘椭圆拟合的锥套图像检测与跟踪[J].中国图象图形学报,2014,19(8):1202-1209)