Amr R. Abdel-Dayem, Ali K. Hamou and Mahmoud R. El-Sakka, "Novel Adaptive Filtering for Salt-and-Pepper Noise Removal From Binary Document Images", International Conference on Image Analysis and Recognition, ICIAR'2004, LNCS 3212, Part 2, pp. 191 - 199, Springer-Verlag Berlin Heidelberg, September 2004, Porto, Portugal.


Noise removal from binary document and graphic images plays a vital role in the success of various applications. These applications include optical character recognition, content-based image retrieval and hand-written recognition systems. In this paper, we present a novel adaptive scheme for noise removal from binary images. The proposed scheme is based on connected component analysis. Simulations over a set of binary images corrupted by 5%, 10% and 15% salt-and-pepper noise showed that this technique reduces the presence of this noise, while preserving fine thread lines that may be removed by other techniques (such as median and morphological filters).