Abstract
Text detection in natural images has gained much attention in the last years as it is a primary step towards fully autonomous text recognition. Understanding the visual text content is of a vital importance in many applicative areas from the internet search engines to the PDA signboard translators. Images of natural scenes, however, pose numerous difficulties compared to the traditional scanned documents. They mainly contain diverse complex text of different sizes, styles and colors with complex backgrounds. Furthermore, such images are captured under variable lighting conditions and are often affected by the skew distortion and perspective projections. In this article an improved edge profile based text detection method is presented. It uses a set of heuristic rules to eliminate detection of non-text areas. The method is evaluated on CVL OCR DB, an annotated image database of text in natural scenes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
