Paper Info
Title
Mobile Visual Search On Printed Documents Using Text And Low Bit-Rate Features
Abstract
We present a novel mobile printed document retrieval system that utilizes both text and low bit-rate features. On the client phone, text are detected using an algorithm based on edge-enhanced Maximally Stable Extremal Regions. The title text image patch is rectified using a gradient based algorithm and recognized using Optical Character Recognition. Low bit-rate image features are extracted from the query image. Both text and compressed features are sent to a server. On the server, the title text is used for on-line search and the features are used for image-based comparison. The proposed system is capable of web-scale document retrieval using title text without the need of constructing a document image database. Using features for image-based comparison, we can reliably match retrieved documents to the query document. Last, by using text and low bit-rate features, we can reduce the transmitted query size significantly.
Year
DOI
Venue
2011
10.1109/ICIP.2011.6116198
2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Keywords
Field
DocType
mobile visual search, image retrieval, document retrieval, document analysis
Computer science,Image retrieval,Artificial intelligence,Document retrieval,Computer vision,Pattern recognition,Information retrieval,Feature (computer vision),Full text search,Optical character recognition,Feature extraction,Maximally stable extremal regions,Visual Word
Conference
ISSN
Citations 
PageRank 
1522-4880
8
0.47
References 
Authors
15
6
Name
Order
Citations
PageRank
Sam S. Tsai172436.51
Huizhong Chen225311.32
David M. Chen394742.62
Georg Schroth425012.71
Radek Grzeszczuk52562204.55
Bernd Girod689881062.96