Indian Journal of Science and Technology
Year: 2017, Volume: 10, Issue: 33, Pages: 1-8
Urooj Beg* , K. Parvathi and Vinod Jha
School of Electronics Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India; [email protected], [email protected], [email protected]
*Author for the correspondence:
School of Electronics Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India; [email protected]
Objective: Braille - a model to reduce the illiteracy rate among the visually challenged people. So, this paper focuses on text translation/ conversion of scanned Hindi document to Braille, a single mode of communication for visually challenged people via Image processing techniques. Method/Analysis: The translation of scanned Hindi text into Braille code involves the following four processes: (i) Hindi database generation of consonants and matras using image segmentation. (ii) Segmentation of test images into lines followed by words and finally into letters. This step involves three types of segmentation: (a) line segmentation (b) word segmentation (c) letter segmentation. (iii) Letter matching of segmented letters with the generated Hindi database using Principal Component Analysis (PCA). (iv) Conversion of matched letter into corresponding Braille code. The algorithm takes test documents as input and reads the letter wise and maps the letters in the corresponding Braille code. Findings: Three Hindi documents containing single, multiple lines are taken as test documents. These test documents are successfully converted into their corresponding Braille code using the proposed algorithm. A lot of research work has been conducted which emphasizes the conversion of scanned Braille code into the text, but the conversion of scanned text to Braille has not been attempted so far. These results are a step further in the field of Braille communication, adding a new way through which Hindi literature can easily be made available to visually impaired people for improving their knowledge and easy access to documents and books as needed. Improvement/Application: The results obtained will provide easy access of Hindi literature to visually challenged people as there is limited availability of Braille textbooks in the market. The memory consumption is very less as the size of each image in Hindi database is 187x128 pixels. This work can be modified for real time applications, like instant conversion of text to Braille using handheld devices.
Keywords: Hindi Braille, Hindi Data Base, Image Processing, Image Segmentation, Letter Matching, Principal Component Analysis, Text Translation
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