Browse > Article
http://dx.doi.org/10.9728/dcs.2016.17.4.219

An Extracting Text Area Using Adaptive Edge Enhanced MSER in Real World Image  

Park, Youngmok (GeongNam Nat'l Univ. of Science and Technology, Institute of Computer Information)
Park, Sunhwa (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.17, no.4, 2016 , pp. 219-226 More about this Journal
Abstract
In our general life, what we recognize information with our human eyes and use it is diverse and massive. But even the current technologies improved by artificial intelligence are exorbitantly deficient comparing to human visual processing ability. Nevertheless, many researchers are trying to get information in everyday life, especially concentrate effort on recognizing information consisted of text. In the fields of recognizing text, to extract the text from the general document is used in some information processing fields, but to extract and recognize the text from real image is deficient too much yet. It is because the real images have many properties like color, size, orientation and something in common. In this paper, we applies an adaptive edge enhanced MSER(Maximally Stable Extremal Regions) to extract the text area in those diverse environments and the scene text, and show that the proposed method is a comparatively nice method with experiments.
Keywords
Adaptive Edge; Text Extraction; MSER; Text Area; Natural Image;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Kang, Le, et al., "Orientation robust text line detection in natural images.", Computer Vision and Pattern Recognition (CVPR), IEEE, 2014.
2 Sung, Myung-Chul, et al., "Scene Text Detection with Robust Character Candidate Extraction Operator.", 13th ICDAR, 2015.
3 Li, Yao, et al., "Characterness: an indicator of text in the wild.", Image Processing, IEEE Transactionson 23.4 : pp.1666-1677, 2014.   DOI
4 Jung, Keechul, et al., "Text information extraction in images and video: a survey.", Pattern recognition 37.5, pp.977-997, 2004.   DOI
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 Int ernational 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 Thresholding", http://www.kerrywong.com/2009/05/07/canny-edge-detection-auto-thresholding/, Sep. 2015.
11 S. H. Park and etc, "AEMSER Using Adaptive Threshold of Canny Operator To Extract Scene Text", J. of Digital Contents Society, Vol. 16, No. 6, pp. 953-961, 2015.