Research of Bayesian underground positioning technology based on SIFT feature
Yu Wang, Xiaojuan Ban, Boyuan Ma, Yifei Guo, Jinglu Bai · 2016
Underground mining environment is harmful and dangerous for humans, thus in recent years, unmanned mining vehicle technique is a study hot spot. Although image processing is widely applied in automatic navigation system, some key techniques cannot meet application requirements in underground mining scenes, there still need more attention, such as inadequate lighting, gradient variation, high dust concentration, etc. This paper describes two novel methods based on Bayesian algorithm and SIFT feature and is devised to solve these problems simultaneously.