Dot Detection of Braille Images Using A Mixture of Beta Distributions

Abstract

Problem statement: Braille is a tactile format of written communication for people with low vision and blindness worldwide. Optical Braille Recognition (OBR) offers many benefits to Braille users and people who work with them. Approach: This study presents an algorithm for detecting dots composing braille characters in an image of embossed braille material obtained by an optical scanner. We assumed that a mixture of Beta distributions could model the histogram of a scanned braille document. The core of the proposed method was the use of stability of thresholding with Beta distribution to initiate the process of thresholds estimation. Segmented Braille image was used to form a grid that contains recto dots and another one that contains verso dots. Results: Braille dots composing characters on both singlesided and double-sided documents were automatically identified from those grids with excellent accuracy. Conclusion: The experiment showed that the proposed method obtained very good results but it requires more testing on different scanned Braille document images.