NDLI: Thai text localization in natural scene images using Convolutional Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Kobchaisawat, T. Chalidabhongse, T.H.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Eng., Chulalongkorn Univ., Bangkok, Thailand (Kobchaisawat, T.; Chalidabhongse, T.H.)
Abstract	Text detection in natural scene images is a challenging problem due to many variations and uncontrollable factors comparing to text detection on scanned document. Unlike the existing Thai text detection methods which focus on using connected component analysis combining with other rule-based techniques to localize text, our proposed method is based on a well-known automatic feature extractor neural networks called Convolutional Neural Networks (CNN). The CNN is first trained with both English and Thai text datasets. A multi-scaled text confidence maps are constructed in order to cope with the text size variations. Some post-processing and Thai text analysis are also employed to acquire text locations in the image. Base on our experimental results, the proposed method can detect English and Thai text from natural scene images with a promising accuracy comparing to the state-of-the-art method.
Starting Page	1
Ending Page	7
File Size	1309959
Page Count	7
File Format	PDF
ISBN	9786163618238
DOI	10.1109/APSIPA.2014.7041775
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-09
Publisher Place	Cambodia
Access Restriction	Subscribed
Rights Holder	Asia-Pacific Signal and Information Processing Ass
Subject Keyword	Decision support systems Text analysis Neural networks Detectors Abstracts Feature extraction Erbium
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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