@Article{JICS-7-235,
author = {Shangbing Gao and Yunyang Yan},
title = {Saliency and Active Contour based Traffic Sign Detection},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {7},
number = {3},
pages = {235--240},
abstract = {In this paper, we propose a new approach to detect salient traffic signs, which is based on visual 
saliency and auto-generated strokes for image segmentation. The proposed algorithm deals with two tasks on 
detecting traffic  signs: auto-location and  auto  extraction.  Firstly,  inspired  by recent  work  of  visual  saliency 
detection,  we  obtain  the  location  of  traffic  signs  in  a  natural  image  by  multi-scale  principle  component 
analysis  (MPCA).  Secondly,  in  order  to  extract  traffic  signs,  auto-generated  strokes  are  used  instead  of 
drawing  the  strokes  by  the  users,  the  sign  board  area  is  extracted  using  localizing  Region-Based  Active 
Contour.  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/22647.html}
}