A binarization method for scanned documents based on hidden Markov model

The binarization stage is a very critical in document analysis since the quality of a binarized image determines the performance of the entire process. However due to many uncertain factors such as complex signal-dependent noise and variable background intensity, which is caused by non-uniform illumination, shadow, smear, smudge or low contrast, an effective binarization algorithm that will work on a broad set of composite documents has yet to be developed. Here we propose a new algorithm which implements hidden Markov model in the binarization stage. The simulation results prove that this method is efficient in extracting information from various noisy backgrounds