In this paper we present a camera phone-based currency reader for the visually impaired that can identify the value of U.S. paper currency. Currently, U.S. paper currency can only be identified visually and this situation will continue for a foreseeable future. Our solution harvests the imaging and computational power on camera phones to read these bills. Considering it is impractical for the visually impaired to capture high quality image, our currency reader performs real time processing for each captured frame as the camera approaches the bill. We developed efficient background subtraction and perspective correction algorithms and trained our currency reader using an efficient Ada-boost framework. Our currency reader processes 10 frames/second and achieves a false positive rate of approximately 10 −4 . Major smart phone platforms, including Symbian and Windows Mobile, are supported.
In REF , Lui proposed a background subtraction and perspective correction algorithm using Ada-boost framework and trained it with 32 pairs of pixels to identify the bill values.
A camera phone based currency reader for the visually impaired
Assets '08
Computer Science