Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10005626,
  title    = {A Neural Approach for Color-Textured Images Segmentation},
  author    = {Khalid Salhi and  El Miloud Jaara and  Mohammed Talibi Alaoui},
  country   = {Morocco},
  institution={University of Mohammed First},
  abstract  = {In this paper, we present a neural approach for
unsupervised natural color-texture image segmentation, which is
based on both Kohonen maps and mathematical morphology, using
a combination of the texture and the image color information of the
image, namely, the fractal features based on fractal dimension are
selected to present the information texture, and the color features
presented in RGB color space. These features are then used to train
the network Kohonen, which will be represented by the underlying
probability density function, the segmentation of this map is made
by morphological watershed transformation. The performance of our
color-texture segmentation approach is compared first, to color-based
methods or texture-based methods only, and then to k-means method.},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {10},
  number    = {10},
  year      = {2016},
  pages     = {1847 - 1850},
  ee        = {http://waset.org/publications/10005626},
  url       = {http://waset.org/Publications?p=118},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 118, 2016},
}