Character Region Detection Using Structural Features of Hangul Vowel

한글 모음의 구조적 특징을 이용한 문자영역 검출 기법

  • Park, Jong-Cheon (Department of Computer Engineering, Chungbuk National University) ;
  • Lee, Keun-Wang (Department of the Multimedia Science, Chungwoon University) ;
  • Park, Hyoung-Keun (Department of Electronic Engineering, Namseoul University)
  • 박종천 (충북대학교 컴퓨터공학과) ;
  • 이근왕 (청운대학교 멀티미디어학과) ;
  • 박형근 (남서울대학교 전자공학과)
  • Received : 2011.01.12
  • Accepted : 2012.02.10
  • Published : 2012.02.29


We proposes the method to detect the Hangul character region from natural image using topological structural feature of Hangul grapheme. First, we transform a natural image to a gray-scale image. Second, feature extraction performed with edge and connected component based method, Edge-based method use a Canny-edge detector and connected component based method applied the local range filtering. Next, if features are not corresponding to the heuristic rule of Hangul character, extracted features filtered out and select candidates of character region. Next, candidates of Hangul character region are merged into one Hangul character using Hangul character merging algorithm. Finally, we detect the final character region by Hangul character class decision algorithm. Experimental result, proposed method could detect a character region effectively in images that contains a complex background and various environments. As a result of the performance evaluation, A proposed method showed advanced results about detection of Hangul character region from mobile image.


Supported by : 청운대학교


  1. N. Ezaki, M. Bulacu, L. Schomaker: Text detection from natural scene images: towards a system for visually impaired persons. In: Proc. of the 17th International Conference on Vol. 2, pp.683-686, 2004
  2. Xiaoqing Liu and Jagath Samarabandu: An Edge-Based Text Region Extraction Algorithm for Indoor Mobile Robot Navigation. In: International Journal of Signal Processing, Vol.3(4), pp.273-280, 2006
  3. Kim, S., Kim D., Y. Ryu, Y., and Kim, G: A Robust License-Plate Extraction Method under Complex Image Conditions, In: Proceedings of International Conference on Pattern Recognition, Vol. 3, pp.216-219, 2002
  4. Smith, M. A. and T. Kanade: Video Skimming for Quick Browsing Based on Audio and Image Characterization. Carnegie Mellon University, Technical Report CMU-CS-95-186, 1995
  5. Chung-Mong Lee, A. Kankanhalli: Automatic Extraction of Characters in Complex Scene Images. International Journal of Pattern Recognition and Artificial Intelligence, Vol.9(1), pp. 67-82, 1995
  6. Canny, J.: A Computational Approach to Edge Detection. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No. 6, pp.679-698, 1986
  7. Park, Jong Cheon. : Detection Method of Character Region Using Hangul Structure from Natural Image, Department of Computer Engineering, Doctoral Thesis, University of Chungbuk National, 2011
  8. Oh, In. Gwan.: Study on the Extraction of Character and Special Character from Hangeul Documents with English, Master's Thesis, Department of Computer Science, University of Kwangwoon, 1993
  9. C. Yi and Y. Tian :Text String Detection from Natural Scenes by Structure-based Partition and Grouping. In : IEEE Transactions on Image Proc., PMID:21411405, 2011
  10. KAIST Scene Text Database,