@article{873,
  author = {Nisar Hundewale},
  title = {Gender Face Classification using Continous Wavelet Transform and Linear Discriminant Analysis},
  journal = {Journal of Intelligent Computing},
  year = {2012},
  volume = {3},
  number = {1},
  doi = {},
  url = {http://www.dline.info/jic/fulltext/v3n1/2.pd},
  abstract = {when we look at a face, we easily identify that person’s gender, expression, personality, age, and charisma. Gender classification such as classifying human face is only challenging for computer, but even hard for human in some cases. In this paper a new Novel approach is proposed to recognize gender from the face image. Continuous Wavelet Transforms are used for features selections for each face images of male and female. These selected features will be used to classify the face images of each Gender using Support Vector Machine (SVM). This Paper use ORL database contain 400 images include both Male and Female Gender. The experimental result shows that the proposed approach (Continuous wavelet Transform (1-D) and Linear Discriminate Analysis achieves excellent classification accuracy (100%).},
}