A scheme for automatic text rectification in real scene images

Baokang Wang; Changsong Liu; Xiaoqing Ding

doi:10.1117/12.2083184

6 March 2015 A scheme for automatic text rectification in real scene images

Baokang Wang, Changsong Liu, Xiaoqing Ding

Proceedings Volume 9408, Imaging and Multimedia Analytics in a Web and Mobile World 2015; 94080M (2015) https://doi.org/10.1117/12.2083184
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Digital camera is gradually replacing traditional flat-bed scanner as the main access to obtain text information for its usability, cheapness and high-resolution, there has been a large amount of research done on camera-based text understanding. Unfortunately, arbitrary position of camera lens related to text area can frequently cause perspective distortion which most OCR systems at present cannot manage, thus creating demand for automatic text rectification. Current rectification-related research mainly focused on document images, distortion of natural scene text is seldom considered. In this paper, a scheme for automatic text rectification in natural scene images is proposed. It relies on geometric information extracted from characters themselves as well as their surroundings. For the first step, linear segments are extracted from interested region, and a J-Linkage based clustering is performed followed by some customized refinement to estimate primary vanishing point(VP)s. To achieve a more comprehensive VP estimation, second stage would be performed by inspecting the internal structure of characters which involves analysis on pixels and connected components of text lines. Finally VPs are verified and used to implement perspective rectification. Experiments demonstrate increase of recognition rate and improvement compared with some related algorithms.

Citation Download Citation

Baokang Wang, Changsong Liu, and Xiaoqing Ding "A scheme for automatic text rectification in real scene images", Proc. SPIE 9408, Imaging and Multimedia Analytics in a Web and Mobile World 2015, 94080M (6 March 2015); https://doi.org/10.1117/12.2083184

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