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http://dx.doi.org/10.9728/dcs.2015.16.6.951

AEMSER Using Adaptive Threshold Of Canny Operator To Extract Scene Text  

Park, Sunhwa (Gyeongsang Univ. Dept. of Computer Science and Graduate School of CCBM)
Kim, Donghyun (Gyeongsang Univ. Dept. of Computer Science)
Im, Hyunsoo (Gyeongsang Univ. Dept. of Computer Science)
Kim, Honghoon (Gyeongsang Univ. Dept. of Computer Science)
Paek, Jaegyung (Gyeongsang Univ. Dept. of Computer Science)
Park, Jaeheung (Gyeongsang Univ. Dept. of Computer Science and Graduate School of CCBM)
Seo, Yeong Geon (Gyeongsang Univ. Dept. of Computer Science and Graduate School of CCBM)
Publication Information
Journal of Digital Contents Society / v.16, no.6, 2015 , pp. 951-959 More about this Journal
Abstract
Scene text extraction is important because it offers some important information on different image based applications pouring in current smart generation. Edge-Enhanced MSER(Maximally Stable Extremal Regions) which enhances the boundaries using the canny operator after extracting the basic MSER shows excellent performance in terms of text extraction. But according to setting the threshold of the canny operator, the result images using Edge-Enhanced MSER are different, so there needs a method figuring out the threshold. In this paper, we propose a AEMSER(Adaptive Edge-enhanced MSER) that applies the method extracting the boundary using the middle value of histogram to Edge-Enhanced MSER to get the canny operator's threshold. The proposed method can acquire better result images than the existing methods because it extracts the area only for the obvious boundaries.
Keywords
MSER; Canny Auto Threshold; Scene Text Extraction; Adaptive Threshold; Threshold Computation;
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  • Reference
1 Li, Yao, et al., "Characterness: an indicator of text in the wild.", Image Processing, IEEE Transactions on 23.4 : pp.1666-1677, 2014.   DOI
2 Jung, Keechul, et al., "Text information extraction in images and video: a survey.", Pattern recognition 37.5, pp.977-997, 2004.   DOI
3 Kang, Le, et al., "Orientation robust text line detection in natural images.", Computer Vision and Pattern Recognition (CVPR), IEEE, 2014.
4 Sung, Myung-Chul, et al., "Scene Text Detection with Robust Character Candidate Extraction Operator.", 13th ICDAR, 2015.
5 Canny, John, "A computational approach to edge detection." IEEE Trans. Pattern Anal. Mach. Intell., vol. 8, pp.679-698, 1986.
6 Fang, Mei, et al., "The study on an application of otsu Operator in canny operator." International Symposium on Information Processing (ISIP). 2009.
7 Chen, H., et al., "Robust text detection in natural images with edge-enhanced maximally stable extremal regions." In Image Processing (ICIP), 18th IEEE International Conference on, pp.2609-2612, Sep. 2011.
8 Upadhyay, Nishchal Gyan, and Kamlesh Lakhwani, "Edge Detection Using Fuzzy Approach Involving Automatic Threshold Generation.", International Journal Of Scientific & Techonology Research Vol. 2, Iss. 7, pp.128-131, July 2013.
9 Epshtein, Boris, et al., "Detecting text in natural scenes with stroke width transform.", Computer Vision and Pattern Recognition, IEEE, 2010.
10 Kerry D. Wong, "Canny Edge Detection Auto Thres holding", http://www.kerrywong.com/2009/05/07/canny-edge-detection-auto-thresholding/, Sep. 2015