@article{780035,
      recid = {780035},
      author = {Gonzalez, Claudia I., and Melin, Patricia, and Castro,  Juan R., and Castillo, Oscar,},
      title = {Edge detection methods based on generalized type-2 fuzzy  logic /},
      pages = {1 online resource :},
      abstract = {In this book four new methods are proposed. In the first  method the generalized type-2 fuzzy logic is combined with  the morphological gra-dient technique. The second method  combines the general type-2 fuzzy systems (GT2 FSs) and the  Sobel operator; in the third approach the me-thodology  based on Sobel operator and GT2 FSs is improved to be  applied on color images. In the fourth approach, we  proposed a novel edge detec-tion method where, a digital  image is converted a generalized type-2 fuzzy image. In  this book it is also included a comparative study of  type-1, inter-val type-2 and generalized type-2 fuzzy  systems as tools to enhance edge detection in digital  images when used in conjunction with the morphologi-cal  gradient and the Sobel operator. The proposed generalized  type-2 fuzzy edge detection methods were tested with  benchmark images and synthetic images, in a grayscale and  color format. Another contribution in this book is that the  generalized type-2 fuzzy edge detector method is applied in  the preprocessing phase of a face rec-ognition system;  where the recognition system is based on a monolithic  neural network. The aim of this part of the book is to show  the advantage of using a generalized type-2 fuzzy edge  detector in pattern recognition applications. The main goal  of using generalized type-2 fuzzy logic in edge detec-tion  applications is to provide them with the ability to handle  uncertainty in processing real world images; otherwise, to  demonstrate that a GT2 FS has a better performance than the  edge detection methods based on type-1 and type-2 fuzzy  logic systems.},
      url = {http://library.usi.edu/record/780035},
      doi = {https://doi.org/10.1007/978-3-319-53994-2},
}