摘要
基于马尔可夫随机场(MRF)图像分割模型,该文提出了一种能够较好分割出表面贴装技术(SMT)焊点区域的分割算法,即基于Gibbs采样的模拟退火算法,并讨论了影响图像分割效果的主要因素,最后将该算法与传统的Gibbs采样算法以及模拟退火算法进行比较。实验结果表明,该算法通过少量人工干预、降低采样维度,从而减少了优化收敛时间,能最快地收敛到全局最优,分割成功率较高,结果较为精确,为进一步的焊点质量分析提供了保证。
Based on Markov random field （MRF） image segmentation frame, this paper presents a better partitioning algorithm for surface mount technology （SMT） solder segmentation which is the simulated annealing algorithm based on Gibbs sampling, and discusses the main factors which affect the segmentation effect. Finally this algorithm is compared with the traditional Gibbs algorithm and simulated annealing algorithm. It is shown from the experiment that the proposed algorithm only needs a few artificial interactions to reduce the sample dimensions and decrease the optimization and convergence time, and it has the fastest convergence speed to obtain the global optimization, with high segmentation success rate and accurate result. The segmentation result provides the guarantee for the further quality analysis of solder joints.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2016年第5期819-823,859,共6页
Journal of University of Electronic Science and Technology of China
基金
河南省科技公关项目(142102210231)
