• DocumentCode
    3019929
  • Title

    A robustness and real-time face detection algorithm in complex background

  • Author

    Lang, Li-ying ; Gu, Wei-wei

  • Author_Institution
    Hebei Univ. of Eng., Handan, China
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    22
  • Lastpage
    25
  • Abstract
    Because AdaBoost cascade face detection algorithm has a very outstanding performance, AdaBoost face detection is the mainstream algorithm currently. But it can produce misjudgment at a similar facial feature regional, particularly in the detection of more complicated image background circumstances misjudgment is even more serious. In view of reasons above, in this paper, a new algorithm was proposed and named A-SCS algorithm, which is increased skin color segmentation after detected face region use the AdaBoost algorithm. This algorithm makes full use of the image useful information, and greatly reduced the possibility of misjudgment. Compare to AdaBoost algorithm and skin color segmentation algorithm, the algorithm mentioned in this paper reduced the false detecting rate in complex background image, At the same time, it is of definite robustness. Simulated experimental results by Matlab indicate that this algorithm is faster and accuracy. Therefore it can be applied to real-time face detection system.
  • Keywords
    image colour analysis; image segmentation; matrix algebra; object detection; A-SCS algorithm; AdaBoost cascade face detection algorithm; Matlab; complex background image; false detecting rate; self-adaptation boosting algorithm; skin color segmentation algorithm; Algorithm design and analysis; Colored noise; Face detection; Image segmentation; Mathematical model; Pattern analysis; Pattern recognition; Robustness; Skin; Wavelet analysis; AdaBoost; Color space; Skin color model; Skin color segmentation; face detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3728-3
  • Electronic_ISBN
    978-1-4244-3729-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2009.5207441
  • Filename
    5207441