• DocumentCode
    632676
  • Title

    Mobile Video Capture of Multi-page Documents

  • Author

    Kumar, Jayant ; Bala, Raja ; Hengzhou Ding ; Emmett, P.

  • Author_Institution
    Univ. of Maryland, College Park, MD, USA
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    35
  • Lastpage
    40
  • Abstract
    This paper presents a mobile application for capturing images of printed multi-page documents with a smartphone camera. With today´s available document capture applications, the user has to carefully capture individual photographs of each page and assemble them into a document, leading to a cumbersome and time consuming user experience. We propose a novel approach of using video to capture multipage documents. Our algorithm automatically selects the best still images corresponding to individual pages of the document from the video. The technique combines video motion analysis, inertial sensor signals, and an image quality (IQ) prediction technique to select the best page images from the video. For the latter, we extend a previous no-reference IQ prediction algorithm to suit the needs of our video application. The algorithm has been implemented on an iPhone 4S. Individual pages are successfully extracted for a wide variety of multi-page documents. OCR analysis shows that the quality of document images produced by our app is comparable to that of standard still captures. At the same time, user studies confirm that in the majority of trials, video capture provides an experience that is faster and more convenient than multiple still captures.
  • Keywords
    image motion analysis; mobile radio; video signal processing; OCR analysis; iPhone 4S; image capture; image quality prediction technique; inertial sensor signals; mobile application; mobile video capture; multipage documents; noreference IQ prediction algorithm; photographs; printed multipage documents; smartphone camera; time consuming user experience; video motion analysis; Accuracy; Cameras; Mobile communication; Optical character recognition software; Prediction algorithms; Support vector machines; Training; Document capture; Document image quality; Video summarization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • Type

    conf

  • DOI
    10.1109/CVPRW.2013.10
  • Filename
    6595848