Main Article Content

M Hanumanthappa


Optical Braille Recognition (OBR), the automated software processes that are used in capturing and converting the Braille documents into text. The image data of embossed Braille plate captured using mobile camera or scanner is the input to OBR. Preprocessing is the first stage performed by OBR system. The Considerable troubles in Image captured using camera, mobile or scanners include low-quality image due to irregular lightness during scanning, relatively low resolution of camera, impulse noise in the image, diverse gray-level values, introduce an elevated spatial frequency, angled or slanted image captured as a result of human error, deformation or warp of image document that continue deprivation or disability of the dots, manifestation of uninvited dots, irregular gap in connecting dots and the cells representing character. These impulse noises are eliminated by applying various image enhancement techniques under preprocessing stage of OBR. The main mission of the paper is to study and provide a proportional learning of diverse preprocessing techniques that are applied to the Braille image by various researchers.


Download data is not yet available.

Article Details

Author Biographies


Research Scholar, Department of Computer Science and Applications

M Hanumanthappa, Bangalore University

Professor, Department of Computer Science and Applications


Abdul Malik S. Al-Salman, Ali El-Zaart, Yousef Al-Suhaibani, Khaled Al-Hokail, Abdu Gumaei, “Designing Braille Copier-Based on Image Processing Techniquesâ€, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-4 Issue-5, November 2014

Aisha Mousa, Hazem Hiary, Raja Alomari, and Loai Alnemer, “Smart Braille System Recognizerâ€, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 6, No 1, November 2013 ISSN (Print): 1694-0814, ISSN (Online): 1694-0784

C. M. Ng, V. Ng and Y. Lau, "Regular feature extraction for recognition of Braille", Computational Intelligence and Multimedia Applications, 1999. ICCIMA '99. Proceedings. Third International Conference on, New Delhi, 1999, pp. 302-306. doi: 10.1109/ ICCIMA. 1999. 798547

Huaxun Zhang, J. Li and J. Yin, "A Research on Paper-Mediated Braille Automatic Extraction Method," Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on, Changsha, China, 2010, pp. 328-331. doi: 10.1109/ICICTA.2010.145

Jie Li and Xiaoguang Yan, "Optical Braille character recognition with Support-Vector Machine classifier," 2010 International Conference on Computer Application and System Modeling (ICCASM 2010), Taiyuan, 2010, pp. V12-219-V12-222, doi: 10.1109/ICCASM.2010.5622245

Jie Li, Xiaoguang Yan and Dayong Zhang, "Optical Braille Recognition with Haar wavelet features and Support-Vector-Machine," 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, Changchun, 2010, pp. 64-67. doi:10.1109/CMCE.2010.5610062

L. Nian-feng and W. Li-rong, "A kind of Braille paper automatic marking system," Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on, Jilin, 2011, pp. 664-667. doi: 10.1109/ MEC. 2011. 6025553

L. Wong, W. Abdulla and S. Hussmann, "A software algorithm prototype for optical recognition of embossed Braille," Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, 2004, pp. 586-589 Vol.2. doi: 10.1109/ICPR.2004.1334316

Mohd. Wajid, M. Waris Abdullah and O. Farooq, "Imprinted Braille-character pattern recognition using image processing techniques," Image Information Processing (ICIIP), 2011 International Conference on, Himachal Pradesh, 2011, pp. 1-5. doi: 10.1109/ICIIP.2011.6108954

T. Li, X. Zeng and S. Xu, "A Deep Learning Method for Braille Recognition", Computational Intelligence and Communication Networks (CICN), 2014 International Conference on, Bhopal, 2014, pp. 1092-1095. doi: 10.1109/ CICN.2014.229.