Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10001173,
  title    = {Maximum Entropy Based Image Segmentation of  Human Skin Lesion },
  author    = {Sheema Shuja Khattak and  Gule Saman and  Imran Khan and  Abdus Salam},
  country   = {Pakistan},
  institution={Abasyn University Peshawar},
  abstract  = {Image segmentation plays an important role in
medical imaging applications. Therefore, accurate methods are
needed for the successful segmentation of medical images for
diagnosis and detection of various diseases. In this paper, we have
used maximum entropy to achieve image segmentation. Maximum
entropy has been calculated using Shannon, Renyi and Tsallis
entropies. This work has novelty based on the detection of skin lesion
caused by the bite of a parasite called Sand Fly causing the disease is
called Cutaneous Leishmaniasis.
},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {9},
  number    = {5},
  year      = {2015},
  pages     = {1094 - 1098},
  ee        = {http://waset.org/publications/10001173},
  url       = {http://waset.org/Publications?p=101},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 101, 2015},
}