Mobile Video Capture of Multi-page Documents

Jayant Kumar, Raja Bala, Hengzhou Ding, Phillip Emmett; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2013, pp. 35-40


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 noreference 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.

Related Material

author = {Kumar, Jayant and Bala, Raja and Ding, Hengzhou and Emmett, Phillip},
title = {Mobile Video Capture of Multi-page Documents},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2013}