Braille document recognition using Belief Propagation

There is a significant need for a system to recognize Braille documents in order to preserve them and make them available to a larger group of visually impaired people. A new system for Braille document recognition is proposed. We introduce a highly-adaptive Braille documents parameters estimation method to automatically determine the rotation angle, indentations, and spacing in both vertical and horizontal orientation. The key element in determining the rotation angle of the images is based on Radon transform. Also we introduce the method of Braille translation using Belief Propagation on the assumption that the Braille document is a Hidden Markov Model. We demonstrate the effectiveness of rotation angle correction as well as the accuracy of indentation and spacing in both orientations. We also prove that the translation algorithm is efficient and robust to errors made in the dot detection. The proposed method may be used for further applications.