Các Nghiên Cứu
PhD Thesis Title: "Incremental and interactive learning for document image - Application for intelligent cognitive scanning of old documents".
Brief Description: We investigate a specific area of document classification in which the documents come as a flow over the time. Moreover, the exact number of classes of document to deal with is not known from the beginning and could evolve over the time. To be able to perform classification task in such area, we need specific classifiers that are able to perform incremental learning and change their modeling over the time. More specifically, we are focusing our study on SVM approaches, known to perform well, and for which incremental (i-SVM) procedures exist. Nevertheless, most of them are only able to deal with a fixed number of classes. So we designed a new incremental learning procedure based on one-class SVMs. This one is able to improve its classification accuracy over the time, with the arrival of new labeled data, without performing any complete retraining. Moreover, when instances are coming with a previously unknown label (appearing of a new class), the training procedure is able to modify the classifier model to recognize this corresponding new kind of documents. Our incremental approach is able: to perform, at each time, as well as a static one-class classifier fully retrained using all previously seen data; to model very quickly and efficiently new incoming classes.
Keywords: scanning; image processing; incremental learning and classification; human-computer interaction.
Master Thesis Title: "Panel and speech balloon extraction from comics books".
Brief Description: Comic books represent an important cultural heritage in many countries. However, few researches have been done in order to analyse the content of comics such as panels, speech balloons or characters. At first glance, the structure of a comic page may appear easy to determine. In practice, the configuration of the page, the size and the shape of the panels can be different from one page to the next. Moreover, authors often draw extended contents (speech balloon or comic art) that overlap two panels or more. In some situations, the panel extraction can become a real challenge. Speech balloons are other important elements of comics. Full text indexing is only possible if the text can be extracted. However the text is usually embedded among graphic elements. Moreover, unlike newspapers, the text layout in speech balloons can be irregular. Classic text extraction method can fail. We propose a method based on region growing and mathematical morphology to extract automatically the panels of a comic page and a method to detect speech balloons.
Keywords: comic book; comics panel extraction; comics page segmentation; region growing, mathematical morphology.
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