Probabilistic estimation of Braille document parameters

Braille is the most common means of reading and study for visually handicapped people. The need for converting Braille documents into a computer-readable format has motivated research into the implementation of Braille recognition systems. The most fundamental steps in such recognition are estimating the scaling, spacing, and skewness properties of a given Braille document. In this paper we propose a statistical method for estimating these parameters, where we model an entire Braille image using a parameterized probability density function and find the maximum-likelihood (ML) estimates using Expectation-Maximization (EM) algorithm. The proposed method is robust against noise and other image artifacts, and has a modest computational complexity for straightforward execution on ordinary personal computers.