Recognition of degraded ancient characters based on dense SIFT
Sajid Saleem, Fabian Hollaus, Robert Sablatnig · 2014
This paper presents a novel method for the recognition of ancient characters in historical documents. The method proposed is especially designed for degraded documents in which the character recognition based on state of the art methods is hard to achieve due to faded out ink, stain and background noise. The method proposed deals with such degradations by making use of the Dense SIFT features and the nearest neighbor distance maps. The maps encode the distances between the features of the documents and the training set. This results in local minima in the nearest neighbor distance maps which help in localization and recognition of characters in the documents. The experiments on three datasets show that the method proposed achieves a better character recognition performance compared to another method designed for similar historical documents.