Skip to main content
  • Research Article
  • Open access
  • Published:

A Multifunctional Reading Assistant for the Visually Impaired


In the growing market of camera phones, new applications for the visually impaired are nowadays being developed thanks to the increasing capabilities of these equipments. The need to access to text is of primary importance for those people in a society driven by information. To meet this need, our project objective was to develop a multifunctional reading assistant for blind community. The main functionality is the recognition of text in mobile situations but the system can also deal with several specific recognition requests such as banknotes or objects through labels. In this paper, the major challenge is to fully meet user requirements taking into account their disability and some limitations of hardware such as poor resolution, blur, and uneven lighting. For these applications, it is necessary to take a satisfactory picture, which may be challenging for some users. Hence, this point has also been considered by proposing a training tutorial based on image processing methods as well. Developed in a user-centered design, text reading applications are described along with detailed results performed on databases mostly acquired by visually impaired users.



  1. Peters J-P, Mancas-Thillou C, Ferreira S: Embedded reading device for blind people: a user-centred design. Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop (AIPR '04), October 2004, Washington, DC, USA 217-222.

    Chapter  Google Scholar 

  2. K-NFB Reader website 2007.

  3. AdvantEdge Reader website 2007.

  4. Zhang J, Chen X, Yang J, Waibel A: A PDA-based sign translator. Proceedings of the 4th IEEE International Conference on Multimodal Interfaces (ICMI '02), October 2002, Pittsburgh, Pa, USA 217-222.

    Chapter  Google Scholar 

  5. Lee ER, Kim PK, Kim HJ: Automatic recognition of a car license plate using color image processing. Proceedings of the IEEE International Conference on Image Processing (ICIP '94), November 1994, Austin, Tex, USA 2: 301-305.

    Google Scholar 

  6. Draghici S: A neural network based artificial vision system for licence plate recognition. International Journal of Neural Systems 1997,8(1):113-126. 10.1142/S0129065797000148

    Article  Google Scholar 

  7. Jain AK, Yu B: Automatic text location in images and video frames. Pattern Recognition 1998,31(12):2055-2076. 10.1016/S0031-3203(98)00067-3

    Article  Google Scholar 

  8. Pietikäinen M, Okun O: Text extraction from grey scale page images by simple edge detectors. Proceedings of the 12th Scandinavian Conference on Image Analysis, June 2001, Bergen, Norway 628-635.

    Google Scholar 

  9. Chen W-Y, Chen S-Y: Adaptive page segmentation for color technical journals' cover images. Image and Vision Computing 1998,16(12-13):855-877. 10.1016/S0262-8856(98)00062-6

    Article  Google Scholar 

  10. Zhong Y, Karu K, Jain AK: Locating text in complex color images. Pattern Recognition 1995,28(10):1523-1535. 10.1016/0031-3203(95)00030-4

    Article  Google Scholar 

  11. Wu V, Manmatha R, Riseman E: Textfinder: an automatic system to detect and recognize text inimages. IEEE Transactions on Pattern Analysis and Machine Intelligence 1999,21(11):1224-1229. 10.1109/34.809116

    Article  Google Scholar 

  12. Jain AK, Bhattacharjee S: Text segmentation using Gabor filters for automatic document processing. Machine Vision and Applications 1992,5(3):169-184. 10.1007/BF02626996

    Article  Google Scholar 

  13. Sezgin M, Sankur B: Survey over image thresholding techniques and quantitative performance evaluation. Journal of Electronic Imaging 2004,13(1):146-168. 10.1117/1.1631315

    Article  Google Scholar 

  14. Abadpour A, Kasaei S: A new parametric linear adaptive color space and its PCA-based implementation. Proceedings of the 9th Annual Computer Society of Iran Computer Conference (CSICC '04), February 2004, Tehran, Iran 2: 125-132.

    Google Scholar 

  15. Garcia C, Apostolidis X: Text detection and segmentation in complex color images. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '00), June 2000, Istanbul, Turkey 4: 2326-2329.

    Google Scholar 

  16. Chen D: Text detection and recognition in images and video sequences, Ph.D. thesis. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; 2003.

    Google Scholar 

  17. Mancas-Thillou C: Natural scene text understanding, Ph.D. thesis. Faculté Polytechnique de Mons, Mons, Belgium; 2007.

    Google Scholar 

  18. Lienhart R, Wernicke A: Localizing and segmenting text in images and videos. IEEE Transactions on Circuits and Systems for Video Technology 2002,12(4):256-268. 10.1109/76.999203

    Article  Google Scholar 

  19. Dunn D, Higgins WE, Wakeley J: Texture segmentation using 2-D Gabor elementary functions. IEEE Transactions on Pattern Analysis and Machine Intelligence 1994,16(2):130-149. 10.1109/34.273736

    Article  Google Scholar 

  20. Jain AK, Farrokhnia F: Unsupervised texture segmentation using Gabor filters. Pattern Recognition 1991,24(12):1167-1186. 10.1016/0031-3203(91)90143-S

    Article  Google Scholar 

  21. Mancas M, Mancas-Thillou C, Gosselin B, Macq B: A rarity-based visual attention map—application to texture description. Proceedings of IEEE International Conference on Image Processing, October 2006, Atlanta, Ga, USA 445-448.

    Google Scholar 

  22. Otsu N: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 1979,9(1):62-66.

    Article  MathSciNet  Google Scholar 

  23. Robust Reading Competition 2007.

  24. Beaufort R, Mancas-Thillou C: A weighted finite-state framework for correcting errors in natural scene OCR. Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR '07), September 2007, Curitiba, Brazil

    Google Scholar 

  25. Daisy website 2007.

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Céline Mancas-Thillou.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Mancas-Thillou, C., Ferreira, S., Demeyer, J. et al. A Multifunctional Reading Assistant for the Visually Impaired. J Image Video Proc 2007, 064295 (2007).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: