@article{5839,
  abstract     = {Canny's edge detection algorithm is a classical and robust method for edge detection in gray-scale images. The two 
significant features of this method are introduction of NMS (Non-Maximum Suppression) and double thresholding of 
the  gradient  image.  Due  to  poor  illumination,  the  region  boundaries  in  an  image  may  become  vague,  creating  
uncertainties  in  the  gradient  image.  In  this  paper,  we  have  proposed  an  algorithm  based  on  the  concept  of  type-2  fuzzy  sets  to  handle  uncertainties  that  automatically  selects  the  threshold  values  needed  to  segment  the  gradient image using classical Canny’s edge detection algorithm. The results show that our algorithm works significantly well on different benchmark images as well as medical images (hand radiography images). },
  author       = {Biswas, Ranita and Sil, Jaya},
  issn         = {2212-0173},
  journal      = {Procedia Technology},
  pages        = {820--824},
  publisher    = {Elsevier},
  title        = {{An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets}},
  doi          = {10.1016/j.protcy.2012.05.134},
  volume       = {4},
  year         = {2012},
}