针对印制电路板(printed circuit board,PCB)光电图像模糊且含噪声的具体情况,提出了改进的边缘信息提取算法.首先分别对自适应模糊集增强算法与数学形态学边缘检测算法(edge detection algorithm of mathematical morphology,EDAMM)实施改进,并分析了其基本原理.然后结合这两种算法对PCB光电图像进行预处理及边缘信息提取.最后对两幅由不同成像系统获取的PCB光电图像进行了边缘信息提取实验.结果表明:用本文算法获得的PCB光电图像明暗对比度较高,并提取了精确且清晰的图像边缘信息,明显减少了噪声,所得图像的优质系数较高,两幅图像的优质系数分别是0.885 2、0.874 9,均高于本文中所提到的另外4种算法的结果.可见,采用本文算法可以更好地去除PCB光电图像中的模糊与噪声,并精确地提取出PCB光电图像的边缘信息.
Edge information extraction for printed circuit board photoelectric image
Aiming at the specific situation of the fuzzy and noisy in the printed circuit board(PCB)photo-electric image,an improved edge information extraction algorithm is presented.Firstly,the adaptive fuzzy set enhancement algorithm and the edge detection algorithm of mathematical morphology(EDAMM)are improved,respectively,and their basic principles are analyzed.Then the two algorithms are combined to preprocess the PCB photoelectric images and extract their edge information.Finally,the experiments for edge information extraction are carried out with two PCB photoelectric images acquired by different ima-ging systems.The results show that the contrasts between light and dark of two images obtained by this algorithm are higher,and the accurate and clear edge information is extracted,the noise is significantly reduced.And the excellent quality coefficient of the obtained image is higher,which are 0.885 2 and 0.874 9 of the two images,there are higher than which of the other four algorithms mentioned in this pa-per,respectively.This shows that our algorithm can better remove the fuzziness and noise of PCB photo-electric images,and it can accurately extract their edge information.
edge information extractionprinted circuit board(PCB)photoelectric imagefuzzy set en-hancementmathematical morphologyexcellent quality coefficient
NETL
NSTL
万方数据
维普
