A Low Complexity Sign Detection and Text Localization Method for Mobile Applications
Abstract
We propose a low complexity method for sign detection and text localization in natural images. This method is designed for mobile applications (e.g., unmanned or handheld devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, or character set. However, the text is assumed to be located on a homogeneous background using a contrasting color. We have deployed our method on a Nokia N800 cellular phone as part of a system for automatic detection and translation of outdoor signs. This handheld device is equipped with a 0.3-megapixel camera capable of acquiring images of outdoor signs that typically contain enough details for the sign to be readable by a human viewer. Our experiments show that the text of these images can be accurately localized within the device in a fraction of a second.
Additional Information
© 2011 IEEE. Manuscript received March 31, 2010; revised October 19, 2010 and February 15, 2011; accepted April 14, 2011. Date of publication May 12, 2011; date of current version September 16, 2011. This work was supported by Next Wave Systems, LLC. Part of this work was presented at ICASSP 2010. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Z. Jane Wang.Additional details
- Eprint ID
- 94486
- DOI
- 10.1109/tmm.2011.2154317
- Resolver ID
- CaltechAUTHORS:20190404-161219653
- Next Wave Systems
- Created
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2019-04-04Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field