Abstract
The detection of texts from natural scene images is a challenge due to the clutter background and variation of illumination and perspective. Among the methods proposed so far, the maximally stable extremal region (MSER) method, as a connected component based one, has been pursued and applied widely. In this paper, we propose an efficient method, called flattening method, to quickly prune the large number of overlapping MSERs, so as to improve the speed and accuracy of MSER-based scene text detection. The method evaluates the character-likeliness of MSERs and retains only one MSER in each path of the MSER tree. Our experimental results on the ICDAR 2013 Robust Reading Dataset demonstrates the effectiveness of the proposed method.
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.
