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A new Bayesian classifier for skin detection

Shirali Shahreza, S ; Sharif University of Technology | 2008

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  1. Type of Document: Article
  2. DOI: 10.1109/ICICIC.2008.54
  3. Publisher: 2008
  4. Abstract:
  5. Skin detection has different applications in computer vision such as face detection, human tracking and adult content filtering. One of the major approaches in pixel based skin detection is using Bayesian classifiers. Bayesian classifiers performance is highly related to their training set. In this paper, we introduce a new Bayesian classifier skin detection method. The main contribution of this paper is creating a huge database to create color probability tables and new method for creating skin pixels data set. Our database consists of about 80000 images containing more than 5 billions pixels. Our tests shows that the performance of Bayesian classifier trained on our data set is better than Compaq data set which is one of the currently greatest data sets. © 2008 IEEE
  6. Keywords:
  7. Artificial intelligence ; Bayesian networks ; Classification (of information) ; Classifiers ; Computer applications ; Computer vision ; Database systems ; Image processing ; Learning systems ; Pixels ; Skin ; Bayesian classifiers ; Content filtering ; Data sets ; Face Detection ; Human tracking ; International conferences ; Probability tables ; Skin detection ; Training sets ; Statistical tests
  8. Source: 3rd International Conference on Innovative Computing Information and Control, ICICIC'08, Dalian, Liaoning, 18 June 2008 through 20 June 2008 ; 2008 ; 9780769531618 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4603361