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http://dx.doi.org/10.15207/JKCS.2019.10.5.027

MSER-based Character detection using contrast differences in natural images  

Kim, Jun Hyeok (Dept of Plasma Bio Display, KwangWoon University)
Lee, Sang Hun (Ingenium College of Liberal Arts, KwangWoon University)
Lee, Gang Seong (Ingenium College of Liberal Arts, KwangWoon University)
Kim, Ki Bong (Department of computer information, Daejeon health institute of technology)
Publication Information
Journal of the Korea Convergence Society / v.10, no.5, 2019 , pp. 27-34 More about this Journal
Abstract
In this paper, we propose a method to remove the background area by analyzing the pattern of the character area. In the character detection result of the MSER(Maximally Stable External Regions) method which distinguishes a region having a constant contrast background regions were detected. To solve this problem, we use the MSER method in natural images, the background is removed by calculating the change rate by searching the character area and the background area which are not different from the areas where the contrast values are different from each other. However, in the background removed image, using the LBP(Local Binary Patterns) method, the area with uniform values in the image was determined to be a character area and character detection was performed. Experiments were carried out with simple images with backgrounds, images with frontal characters, and images with slanted images. The proposed method has a high detection rate of 1.73% compared with the conventional MSER and MSER + LBP method.
Keywords
Contrast; Texture; Gaussian; MSER; LBP; Remove background;
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Times Cited By KSCI : 5  (Citation Analysis)
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