Journal of Korea Society of Industrial Information Systems (한국산업정보학회논문지)

Korea Society of Industrial Information Systems (한국산업정보학회)
권호 표지
DOI QR코드

DOI QR Code

An Optical Character Recognition Method using a Smartphone Gyro Sensor for Visually Impaired Persons

스마트폰 자이로센서를 이용한 시각장애인용 광학문자인식 방법

  • 권순각 (동의대학교 컴퓨터소프트웨어공학과) ;
  • 김흥준 (동의대학교 컴퓨터소프트웨어공학과)
  • Received : 2016.08.14
  • Accepted : 2016.08.31
  • Published : 2016.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

It is possible to implement an optical character recognition system using a high-resolution camera mounted on smart phones in the modern society. Further, characters extracted from the implemented application is possible to provide the voice service for the visually impaired person by using TTS. But, it is difficult for the visually impaired person to properly shoot the objects that character information are included, because it is very hard to accurately understand the current state of the object. In this paper, we propose a method of inducing an appropriate shooting for the visually impaired persons by using a smartphone gyro sensor. As a result of simulation using the implemented program, we were able to see that it is possible to recognize the more character from the same object using the proposed method.

현대 사회에서 스마트폰은 장착된 고화질의 카메라를 이용하여 광학문자인식시스템을 구현할 수 있다. 광학문자시스템으로부터 인식된 문자들은 또한 TTS를 이용하여 시각장애인들에게 음성 서비스를 제공할 수 있다. 문자 정보가 들어있는 객체에 대하여 스마트 폰 카메라를 사용하여 촬영하는 것도 시각장애인들에게는 다소 어려운 일이다. 왜냐하면 피사체의 촬영 이미지를 볼 수가 없기 때문이다. 이러한 문제점을 해결하기 위하여 본 논문에서는 스마트폰의 자이로 센서를 사용하여 시각장애인들의 올바른 촬영을 유도하는 방법을 제안한다. 구현된 프로그램을 사용하여 모의 실험한 결과, 제안된 방법은 같은 객체로부터 보다 많은 문자를 인식하는 것을 확인할 수 있었다.

Keywords

References

  1. J. I. Jung, H. G. Kim, and J. S. Cho, "Design and implementation of a real-time education assistive technology system based on haptic display to improve education environment of total blindness people," Journal of The Korea Contents Society, Vol. 11, No.12, pp.94-102, 2011. https://doi.org/10.5392/JKCA.2011.11.12.094
  2. H. Y. Oh, "Implementation of mobile web interface design for smart-phone users," Journal of The Korea Contents Society, Vol. 11, No.12, pp.639-638, 2011. https://doi.org/10.5392/JKCA.2011.11.12.639
  3. K. A. Cha and S. D. Yeo, "Smart phone application development for aware of unexpected conditions using accelerometer sensors," Journal of the Korea Industrial Information Systems Research, Vol. 17, No.5, pp. 1-8, 2012. https://doi.org/10.9723/JKSIIS.2012.17.5.001
  4. J. T. Ryu, "The development of fall detection system using 3-axis acceleration sensor and tilt sensor," Journal of the Korea Industrial Information Systems Research, Vol. 18, No.4, pp. 19-24, 2013. https://doi.org/10.9723/jksiis.2013.18.4.019
  5. J. J. Kim, S. J. Shin and I. Ryu, "The effect of user perceived-value on intention to use for mobile application service", The Journal of Internet Electronic Commerce Research, Vol. 13, No.3, 2013.
  6. S. K. Kwon, "Speech synthesis system for detected objects by smart phone," Journal of Korea Multimedia Society, Vol. 19, No.2, pp.469-478, 2016. https://doi.org/10.9717/kmms.2016.19.2.469
  7. Y. J. Choi and K. H. Hong, "A study for the accessibility of camera-based mobile applications on touch screen devices for blind people," Journal of The HCI Society of Korea, Vol. 7, No.2, pp.49-56, 2012. https://doi.org/10.17210/jhsk.2012.11.7.2.49
  8. M. J. Lee and K. H. Hong, "Design and implementation of a usability testing tool for user-oriented design of command-and-control voice user interfaces," Journal of The Korean Association of Speech Sciences, Vol. 3, No.2, pp.79-87, 2011.
  9. K. S. Kim, S. C. Park, and S. H. Oh, "Suggestion of enhanced Korean character recognition technique using Google Tesseract open API," Proceedings of Korean Society For Internet Information, pp.249-250, 2015.
  10. E. B. Go, Y. J. Ha, S. R. Choi, K. H. Lee, and Y. H. Park, "An implementation of an Android mobile system for extracting and retrieving texts from images," Journal of Digital Contents Society, Vol. 12, No.1, pp.57-67, 2011. https://doi.org/10.9728/dcs.2011.12.1.057
  11. S. O'Brien and D. B. Haddej, "Optical character recognition," Diss. Worcester Polytechnic Institute, MA., U.S.A, 2012.
  12. R. Smith, "Tesseract OCR engine," Lecture. Google Inc, California, U.S.A, 2007.
  13. A. Abdulkader, and M. R. Cassey, "Low cost correction of OCR errors using learning in a multi-engine environment," Proceedings of IEEE International Conference on Document Analysis and Recognition, pp.576-580, 2009.
  14. T. M. Breuel, A. Ul-Hasan, M. A. Azawi, and F. Shafait, "High-performance OCR for printed English and fraktur using LSTM networks," Proceedings of IEEE International Conference on Document Analysis and Recognition, 2013.
  15. S. Vijayarani and A. Sakila, "Performance comparison of OCR tools," International Journal of UbiComp, Vol. 6, No.3, pp.19-30, 2015. https://doi.org/10.5121/iju.2015.6303