@Article{JICS-9-233,
author = {Yan Zhang ,Shangbing Gao, Shiliang Xu and Yue Zhang},
title = {The Traffic Sign Detection based on the visual saliency},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {9},
number = {3},
pages = {233--240},
abstract = {In this paper, we propose a new approach to detect salient traffic signs, which is based on visual 
saliency and the auto segmentation method based on region merging. The proposed algorithm introduces the 
visual  saliency  model,  and  puts  forward  the  top-down  and  bottom-up  two-way  fusion  mechanism,  tried  to 
consciously  take  the  initiative  to  find  and  simulate  human  visual  unconscious  passive  visual  process  by 
attracting interact. Then the segmentation method based on region merging is used to extract the traffic sign. 
Experiments show that the two-way fusion mechanism in target detection has fast processing speed and high 
accuracy.  Extensive  experiments  on  public  datasets  show  that  our  approach  outperforms  state-of-the-art 
methods  remarkably  in  salient  traffic  sign  detection.  Moreover,  the  proposed  detection  method  has  higher 
accurate rate and robustness to different natural scenes. 
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22583.html}
}