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Mobile visual search on printed documents using text and low bit-rate features

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6 Author(s)
Sam S. Tsai ; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA ; Huizhong Chen ; David Chen ; Georg Schroth
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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.

Published in:

2011 18th IEEE International Conference on Image Processing

Date of Conference:

11-14 Sept. 2011