• DocumentCode
    1841621
  • Title

    Video Mosaic Block Detection Based on Template Matching and SVM

  • Author

    Huang, Xiaodong ; Ma, Huadong ; Yuan, Haidong

  • Author_Institution
    Beijing Key Lab. of Intell. Telecommun. Software & Multimedia, Beijing Univ. of Posts & Telecommun., Beijing
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    1082
  • Lastpage
    1086
  • Abstract
    Mosaic block is easily occurred in the TV signals, which will cause the degraded video. In this paper, we propose an automatic degraded video detection approach based on support vector machine and template matching to detecting mosaic block in video. We develop a detection algorithm based on a cascade of processing steps as follows. First, we use DWT to remove the vertical high frequency of a frame and use the Canny edge algorithm to detect the frame. Second, we use the template matching to find the candidate mosaic block coordinate. Third, a SVM classifier is employed to distinguish mosaic block from the candidate ones. When the number of mosaic block is higher than a threshold, we can regard the frame as the frame with mosaic block. Experimental results show that the proposed algorithm has good performance.
  • Keywords
    discrete wavelet transforms; edge detection; image classification; image matching; image segmentation; support vector machines; video signal processing; Canny edge algorithm; SVM classifier; TV signal; candidate blocking artifact coordinate; discrete wavelet transform; support vector machine; template matching; video mosaic block detection; Degradation; Detectors; Histograms; Image restoration; Machine intelligence; Motion estimation; Support vector machines; Telecommunication computing; Video compression; Videoconference; SVM; degraded video; mosaic blocking; template matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.69
  • Filename
    4709125