• DocumentCode
    3267507
  • Title

    Nude Image Detection Based on SVM

  • Author

    Xinlu Wang ; Xiaojuan Li ; Xiaobo Liu

  • Author_Institution
    Dept. of Inf. Eng. Coll., Capital Normal Univ., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    178
  • Lastpage
    181
  • Abstract
    On the Internet, the nude images caused the spread of a large number of social problems, how to identify the nude image accurately is a problem needing to be solved urgently. Therefore, we integrate both image processing method and support vector machines (SVM), this paper studies a new and enhanced approach on recognition of nude image, namely, combine a face detection model, skin color model and texture model, extract six nude image feature vectors. Additionally, some important factors of SVM are fixed by experiments, such as the training set, kernel function and the cost. The experimental results demonstrate that performing SVM-based nude image detective classification more effective in that it improves the prediction accuracies at the same time.
  • Keywords
    Internet; feature extraction; image colour analysis; image enhancement; image recognition; image texture; object detection; support vector machines; Internet; SVM; face detection model; feature vector extraction; image enhancement; image processing method; image recognition; kernel function; nude image detection; skin color model; support vector machines; texture model; training set; Color; Face detection; Face recognition; Image processing; Image recognition; Internet; Kernel; Skin; Support vector machine classification; Support vector machines; SVM; color model; face detection model; feature vectors; nude image detective; texture model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.148
  • Filename
    5231169