Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/11279,
  title    = {Investigation on Feature Extraction and Classification of Medical Images},
  author    = {P. Gnanasekar and  A. Nagappan and  S. Sharavanan and  O. Saravanan and  D. Vinodkumar and  T. Elayabharathi and  G. Karthik},
  country   = {},
  institution={},
  abstract  = {In this paper we present the deep study about the Bio-
Medical Images and tag it with some basic extracting features (e.g.
color, pixel value etc). The classification is done by using a nearest
neighbor classifier with various distance measures as well as the
automatic combination of classifier results. This process selects a
subset of relevant features from a group of features of the image. It
also helps to acquire better understanding about the image by
describing which the important features are. The accuracy can be
improved by increasing the number of features selected. Various
types of classifications were evolved for the medical images like
Support Vector Machine (SVM) which is used for classifying the
Bacterial types. Ant Colony Optimization method is used for optimal
results. It has high approximation capability and much faster
convergence, Texture feature extraction method based on Gabor
wavelets etc..},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {5},
  number    = {12},
  year      = {2011},
  pages     = {1506 - 1511},
  ee        = {http://waset.org/publications/11279},
  url       = {http://waset.org/Publications?p=60},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 60, 2011},
}