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
Link To Document :
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