Complex analysis of historical documents, application to lettrines
In the general context of cultural heritage preservation campaigns, many digitization projects are being conducted in France and Europe to save the contents of thousands of ancient documents. Images of these documents are used by historians to identify the history of books. This thesis was led into the Navidomass project (ANR-06-MDCA-012) which aims at promoting the written heritage of the documents from the Renaissance, by proposing to identify its images. As part of this thesis, we are particularly interested in graphical images, and more specifically to dropcaps. These graphical images, which emerged with the beginning of printing, are complex images which can be seen as composed of different layers of information (images composed of strokes). To address this problem, we propose an ontological model of complex analysis of images of old documents. This model allows to integrate the knowledge specific to historians, and the knowledge extracted by image processing, into a single database. Due to the complex nature of these images, the usual methods of image analysis and automatic extraction of knowledge are inefficient. We therefore propose a new approach for analyzing images of old documents that can be characterized on their features basis. This approach begins by simplifying the images, separated in different layers of information (shapes and lines). Then, for each layer, we extract patterns used to describe the images. Thus, images are described with most common bags of patterns, and bags of stroke. For these two layers of information, we have also extracted graphs of regions that allow extracting a more structural knowledge of the images. A more complex description is then inserted into the knowledge base in order to allow complex queries. The purpose of this database is to offer the possiblity to make either query by example, or query by specific features of the images, to user.