@article{1028,
  author = {Hlaing Htake Khaung Tin},
  title = {Perceived Gender Classification from Face Images},
  journal = {Journal of Intelligent Computing},
  year = {2012},
  volume = {3},
  number = {3},
  doi = {},
  url = {http://www.dline.info/jic/fulltext/v3n3/3.pdf},
  abstract = {In this paper, a fast and efficient gender classification system based on facial features is proposed to classify the gender. Facial feature extraction is one of the most important and attempted problems in computer vision. It is a necessary step in face recognition, facial image compression. There are many methods have been proposed in the literature for the facial features and gender classification. However, all of them have still disadvantage such as not complete reflection about face structure, face texture. This technique applies to both face alignment and recognition and significantly improves three aspects. First, we introduce shape description for face model. Second, the feature extraction phase, two geometric features are evaluated as the ratios of the distances between eyes, noses, and mouths. Finally, we classified the gender based on the association of two methods: geometric feature based method and Independent Component Analysis (PCA) method for improving the efficiency of facial feature extraction stage. The algorithm has also been tested in practice with a webcam, giving (near) real-time performance and good extraction results},
}