Character Segmentation and Recognition Algorithm for Various Text Region Images

다양한 문자열영상의 개별문자분리 및 인식 알고리즘

  • 구근휘 (포항공대 전자전기공학과) ;
  • 최성후 (포항공대 전자전기공학과) ;
  • 윤종필 (포항공대 전자전기공학과) ;
  • 최종현 (포항공대 전자전기공학과) ;
  • 김상우 (포항공대 전자전기공학과)
  • Published : 2009.04.01

Abstract

Character recognition system consists of four step; text localization, text segmentation, character segmentation, and recognition. The character segmentation is very important and difficult because of noise, illumination, and so on. For high recognition rates of the system, it is necessary to take good performance of character segmentation algorithm. Many algorithms for character segmentation have been developed up to now, and many people have been recently making researches in segmentation of touching or overlapping character. Most of algorithms cannot apply to the text regions of management number marked on the slab in steel image, because the text regions are irregular such as touching character by strong illumination and by trouble of nozzle in marking machine, and loss of character. It is difficult to gain high success rate in various cases. This paper describes a new algorithm of character segmentation to recognize slab management number marked on the slab in the steel image. It is very important that pre-processing step is to convert gray image to binary image without loss of character and touching character. In this binary image, non-touching characters are simply separated by using vertical projection profile. For separating touching characters, after we use combined profile to find candidate points of boundary, decide real character boundary by using method based on recognition. In recognition step, we remove noise of character images, then recognize respective character images. In this paper, the proposed algorithm is effective for character segmentation and recognition of various text regions on the slab in steel image.

References

  1. Yi-Kai Chen, and Jhing-Fa Wang, 'Segmentation of Single- or Multiple-Touching Handwritten Numeral String Using Background and Foreground Analysis', IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 22, no. 11, Nov., 2000
  2. A. Ariyoshi, 'A Character Segmentation Method for Japanese Documents Coping with Touching Character Problems,' Proc. 31th Int'l Conf. Pattern Recognition, The Hague. Netherlands, pp. 313-316, Aug. 1992
  3. N. Otsu, 'A Threshold Selection Method from GrayLevel Histogram', IEEE Trans. Systems, Man and Cybernetics, vol. 1, no. 9, pp. 62-69, 1979
  4. Nello Cristianini and John Shawe-Talyor, 'An Introduction to Support Vector Machines', Cambridge University Press, 2000
  5. SungHoo Choi, Jong Pil Yun, KeunHwi Koo, Jong Hyun Choi Sang Woo Kim, 'Text Region Extraction Algorithm On Steel Making Process', 8th WSEAS Int. Conf. on ROCOM'08, Hangzhou, China, April 6-8, 2008
  6. 이영교, 장유진, 김연탁, 김상우, '빌렛에서의 필기체 인식 시스템 개발', 2006 제어자동화시스템 심포지엄 CASS'2006, 1-3, June, 2006
  7. 최성후, 윤종필, 박영수, 박지훈, 구근휘, 김상우, '슬라브 제품 정보 인식을 위한 문자 분리 및 문자 인식 알고리즘 개발', 2007 정보 및 제어 심포지움 ICS'07, 27-28, Apr., 2007
  8. Richard G. Casey and Eric Lecolinet, 'A Survey of Methods and Strategies in Character Segmentation', IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 18, no. 7, July, 1996 https://doi.org/10.1109/34.506792
  9. Jin Hak Bae, Kee Chul Jung, Jin Wook Kim, and Hang Joon Kim, 'Segmentation of touching characters using an MLP', Pattern Recognition Letters, vol. 19, no. 8, pp. 701-709, 1998 https://doi.org/10.1016/S0167-8655(98)00048-8
  10. Seong-Whan Lee, Dong-June Lee, and Hee-Seon Park, 'A New Methodology for Gray-Scale Character Segmentation and Recognition', IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 18, no. 10, Oct., 1996 https://doi.org/10.1109/34.541415
  11. 홍기상, 장정훈, 양종렬, 김승진, 김태원, '슬라브 번호 인식 장치의 개발', 제어. 자동화. 시스템공학회지, 제2권, 제6호, pp. 63-76, 1996
  12. Rafael C. Gonzalez and Richard E. Woods, 'Digital Image Processing, Second Edition', Prentice Hall
  13. C. Mancas-Thillou and B. Gosselin, 'Character segmentation--by-recognition using log-gabor filters', in Proc. ICPR, Hong Kong, China, 2006, vol. 2, pp. 901-904 https://doi.org/10.1109/ICPR.2006.362
  14. Seong--Whan Lee and Young Joon Kim, 'Direct Extraction of Topographic Features for Gray Scale Character Recognition', IEEE Trans. On Pattern Analysis And Machine Intelligence, vol. 17, no. 7, July, 1995 https://doi.org/10.1109/34.391416