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). © Springer-Verlag 2004.
CITATION STYLE
Abdel-Dayem, A. R., Hamou, A. K., & El-Sakka, M. R. (2004). Novel Adaptive Filtering for Salt-and-Pepper Noise Removal from Binary Document Images. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3212, 191–199. https://doi.org/10.1007/978-3-540-30126-4_24
Mendeley helps you to discover research relevant for your work.