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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
Braille, Connected Component Labelling, Eight-Connectivity, OBR, Recto, Verso.
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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Mr. Shreekanth T
Research Scholar, JSS Research Foundation, Mysore, India. - India
Professor V. Udayashankara
Professor, Department of IT, SJCE, Mysore, India. - India