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http://dx.doi.org/10.15207/JKCS.2018.9.11.061

A Study on Extraction of text region using shape analysis of text in natural scene image  

Yang, Jae-Ho (Dept of Plasma Bio Display, KwangWoon University)
Han, Hyun-Ho (Dept of Plasma Bio Display, KwangWoon University)
Kim, Ki-Bong (Department of computer information, Daejeon health institute of technology)
Lee, Sang-Hun (Ingenium college of liberal arts, Kwangwoon university)
Publication Information
Journal of the Korea Convergence Society / v.9, no.11, 2018 , pp. 61-68 More about this Journal
Abstract
In this paper, we propose a method of character detection by analyzing image enhancement and character type to detect characters in natural images that can be acquired in everyday life. The proposed method emphasizes the boundaries of the object part using the unsharp mask in order to improve the detection rate of the area to be recognized as a character in a natural image. By using the boundary of the enhanced object, the character candidate region of the image is detected using Maximal Stable Extermal Regions (MSER). In order to detect the region to be judged as a real character in the detected character candidate region, the shape of each region is analyzed and the non-character region other than the region having the character characteristic is removed to increase the detection rate of the actual character region. In order to compare the objective test of this paper, we compare the detection rate and the accuracy of the character region with the existing methods. Experimental results show that the proposed method improves the detection rate and accuracy of the character region over the existing character detection method.
Keywords
Text Extraction; Improved Object Edge; MSER Algorithm; Text Pattern; Unsharp Mask;
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