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An Application of Eight Connectivity based Two-pass Connected-Component Labelling Algorithm For Double Sided Braille Dot Recognition
Shreekanth T, V. Udayashankara
Pages - 294 - 312     |    Revised - 10-08-2014     |    Published - 15-09-2014
Volume - 8   Issue - 5    |    Publication Date - September / October 2014  Table of Contents
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KEYWORDS
Braille, Connected Component Labelling, Eight-Connectivity, OBR, Recto, Verso.
ABSTRACT
The intrinsic noise present in the image during the acquisition phase marks the recognition of Braille dots a challenging task in Optical Braille Recognition (OBR). Further, while the Braille document is being embossed on either side in the case of Inter-Point Braille, this problem of Braille dot recognition is aggravated and it makes the differentiation between recto (convex) dots and verso (concave) dots more complex. Also, the recognition of Braille dots should be carried out by reading information recorded on both sides of paper by scanning only one side. This work proposes a novelty to circumvent this issue for distinguishing convex points from concave points even if they are adjacent to each other by using only the shadow patterns of the dots and by employing the connected component labelling using two-pass algorithm and the eight connectivity property of a pixel. Enthused by the fact that, during the acquisition phase, the reflection of light through the verso dots results in a high pixel count for them when compared to the recto dots, this technique works perfectly well with good quality Braille. Furthermore, due to the natural problems like ageing and frequent usage of the document the Braille dots tend to deteriorate resulting in the down fall of the performance of the algorithm for the Braille image. Besides to this for the recognition of the Braille cell in a Braille document with some special cases an adaptive grid construction technique has also been proposed. The results extracted reveal that the enactment of the proposed technique is much consistent and dependable and that the accuracy is very much comparable to the modern state of the art techniques.
CITED BY (3)  
1 Isayed, S., & Tahboub, R. (2015, March). A review of optical Braille recognition. In Web Applications and Networking (WSWAN), 2015 2nd World Symposium on (pp. 1-6). IEEE.
2 Shreekanth, T., & Udayashankara, V. (2015). A Histogram-Based Two-Stage Adaptive Character Segmentation for Transcription of Inter-Point Hindi Braille to Text. International Journal of Image and Graphics, 15(03), 1550012.
3 Barbosa, M. B. B. C. B., & Barbosa, A. F. MuSSE: a tool to extract meta-data from game sprite sheets using Blob detection algorithm.
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1 J. Mennens, L. Van Tichelen, G. Francosis and J. Engelen. “Optical recognition of Braille writing”, Proceedings of second international conference on Document analysis and Recognition, IEEE Oct-1993, pp 428-431.
2 J. Mennens, L. Van Tichelen, G. Francosis and J. Engelen. “Optical Recognition of Braille Writing Using Standard Equipment”, IEEE transactions of rehabilitation engineering, Vol. 2,No. 4, Dec 1994.
3 T. W .Hentzschel, and P. Blenkhorn. “An Optical Reading Systems for Embossed Braille Characters using a Twin Shadows Approach”, Journal of Microcomputer Applications, 1995, pp. 341-345.
4 R .T. Ritchings, A. Antonacopoulos and D .Drakopoulos. “Analysis of Scanned Braille Documents”, In: Dengel, A., Spitz, A.L. (eds.): Document Analysis Systems, World Scientific Publishing Company 1995, pp. 413–421.
5 Y. Oyama, T. Tajima, and H. Koga. “Character Recognition of Mixed Convex- Concave Braille Points and Legibility of Deteriorated Braille Points”, System and Computer in Japan,Vol. 28, No. 2, 1997.
6 C. M. Ng, V.Ng and Y.Lau. “Regular feature extraction for recognition of Braille”, Third International conference on computational Intelligence and Multimedia Applications, 1999,pp. 302—306.
7 A. Antonacopoulos and D. Bridson. “A Robust Braille Recognition System”, Document Analysis Systems VI, A. Dengel and S. Marinai (Eds.), Springer Lecture Notes in Computer Science, LNCS 3163, 2004, pp. 533-545.
8 L. Wong, W. Abdulla and S. Hussmann. “A Software Algorithm Prototype for Optical Recognition of Embossed Braille”, 17th Conference of the International Conference in Pattern Recognition, Cambridge, UK, IEEE-2004, pp. 23–26.
9 N. Falcon, C. M. Travieso, J. B. Alonso and M. A. Ferrer. "Image Processing Techniques for Braille writing Recognitor", EUROCAST 2005, LNCS 3643.
10 A. Malik Al-Salman, Y. ALOHAI, M. Alkanhal and A. Airajith. “An Arabic Optical Braille Recognition System”, ICTA Apr 2007, pp.12-14.
11 A. Malik S. Al-Salman, A. El-Zaart, Y. Al-Suhaibani, K. Al-Hokail and A. O. Al-Qabbany. “An Efficient Braille Cells Recognition”, IEEE-2010.
12 J. Yin, L. Wang and J. Li. “The Research on Paper-mediated Braille Automatic Recognition Method”, Fifth International Conference on Frontier of Computer Science and Technology,IEEE-2010, pp 619-624.
13 J. Li, X. Yan. “Optical Braille Character Recognition with Support-Vector Machine Classifier”, International Conference on Computer Application and System Modelling (ICCASM 2010).
14 S. D. Al-Shamma and S. Fathi. “Arabic Braille Recognition and Transcription into Text and Voice”, 5th Cairo International Biomedical Engineering Conference Cairo, Egypt, IEEEDec 2010.
15 Z. Tai, S. Cheng, P. K. Verma and Y. Zhai. "Braille document recognition using Belief Propagation", Journal of Visual Communication and Image Representation 21(7): 722-730(2010)
16 A. Al-Saleh, A. El-Zaart and A. Malik Al-Salman. “Dot Detection of Braille Images Using A Mixture of Beta Distributions”, 2011 Journal of Computer Science ISSN 1549-3636 pp-1749-1759.
17 J. Bhattacharya, S.Majumder and G.Sanyal. “Automatic Inspection of Braille character: A Vision based approach”, International Journal of computer and Organization trends –volume1, Issue3 -2011, ISSN: 2249-2593, pp. 19-26
18 M. Wajid, M. Waris Abdullah and O. Farooq. “Imprinted Braille-Character Pattern Recognition using Image Processing Techniques”, International Conference on Image Information Processing, IEEE- 2011.
19 R. Ismail Zaghloul and T. Jameel Bani-Ata. “Braille Recognition System – With a Case Study Arabic Braille Documents”, European Journal of Scientific Research, ISSN 1450-216X Vol.62 No.1 (2011), pp. 116-122.
20 L. Di Stefano and A. Bulgarelli. "A Simple and Efficient Connected Components Labeling Algorithm". Proceedings ICIAP, IEEE- 1999, Venice, Italy, pp. 322-327.
21 R.C.Gonzalez and R.E. Woods. “Digital Image Processing”, 2nd edition, Prentice Hall,2002.
Mr. Shreekanth T
Research Scholar, JSS Research Foundation, Mysore, India. - India
speak2shree@gmail.com
Professor V. Udayashankara
Professor, Department of IT, SJCE, Mysore, India. - India