Picture extraction from digitized historical manuscripts
Proceedings of the ACM International Conference on Image and Video Retrieval
Relational indexing of vectorial primitives for symbol spotting in line-drawing images
Pattern Recognition Letters
Surfing on artistic documents with visually assisted tagging
Proceedings of the international conference on Multimedia
Automatic segmentation of digitalized historical manuscripts
Multimedia Tools and Applications
A novel statistical feature extraction method for textual images: Optical font recognition
Expert Systems with Applications: An International Journal
Texture feature evaluation for segmentation of historical document images
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing
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In this article, we propose a method of characterization of images of old documents based on a texture approach. This characterization is carried out with the help of a multi-resolution study of the textures contained in the images of the document. Thus, by extracting five features linked to the frequencies and to the orientations in the different areas of a page, it is possible to extract and compare elements of high semantic level without expressing any hypothesis about the physical or logical structure of the analyzed documents. Experimentation based on segmentation, data analysis and document image retrieval tools demonstrate the performance of our propositions and the advances that they represent in terms of characterization of content of a deeply heterogeneous corpus.