DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Markov random field based binarization for hand-held devices captured document images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Robust text and drawing segmentation algorithm for historical documents
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing
| Hi-index | 0.00 |
In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images.