A structural representation for understanding line-drawing images

International audienceIn this paper, we are concerned with the problem of finding a good and homogeneous representation to encode line-drawing documents (which may be handwritten). We propose a method in which the problems induced by a first-step skeletonization have been avoided. First, we vectorize the image, to get a fine description of the drawing, using only vectors and quadrilateral primitives. A structural graph is built with the primitives extracted from the initial line-drawing image. The objective is to manage attributes relative to elementary objects so as to provide a description of the spatial relationships (inclusion, junction, intersection, etc.) that exist between the graphics in the images. This is done with a representation that provides a global vision of the drawings. The capacity of the representation to evolve and to carry highly semantic information is also highlighted. Finally, we show how an architecture using this structural representation and a mechanism of perceptive cycles can lead to a high-quality interpretation of line drawings

Contributions au tri automatique de documents et de courrier d'entreprises

Ce travail de thèse s inscrit dans le cadre du développement de systèmes de vision industrielle pour le tri automatique de documents et de courriers d entreprises. Les architectures existantes, dont nous avons balayé les spécificités dans les trois premiers chapitres de la thèse, présentent des faiblesses qui se traduisent par des erreurs de lecture et des rejets que l on impute encore trop souvent aux OCR. Or, les étapes responsables de ces rejets et de ces erreurs de lecture sont les premières à intervenir dans le processus. Nous avons ainsi choisi de porter notre contribution sur les aspects inhérents à la segmentation des images de courriers et la localisation de leurs régions d intérêt en investissant une nouvelle approche pyramidale de modélisation par coloration hiérarchique de graphes ; à ce jour, la coloration de graphes n a jamais été exploitée dans un tel contexte. Elle intervient dans notre contribution à toutes les étapes d analyse de la structure des documents ainsi que dans la prise de décision pour la reconnaissance (reconnaissance de la nature du document à traiter et reconnaissance du bloc adresse). Notre architecture a été conçue pour réaliser essentiellement les étapes d analyse de structures et de reconnaissance en garantissant une réelle coopération entres les différents modules d analyse et de décision. Elle s articule autour de trois grandes parties : une partie de segmentation bas niveau (binarisation et recherche de connexités), une partie d extraction de la structure physique par coloration hiérarchique de graphe et une partie de localisation de blocs adresse et de classification de documents. Les algorithmes impliqués dans le système ont été conçus pour leur rapidité d exécution (en adéquation avec les contraintes de temps réels), leur robustesse, et leur compatibilité. Les expérimentations réalisées dans ce contexte sont très encourageantes et offrent également de nouvelles perspectives à une plus grande diversité d images de documents.This thesis deals with the development of industrial vision systems for automatic business documents and mail sorting. These systems need very high processing time, accuracy and precision of results. The current systems are most of time made of sequential modules needing fast and efficient algorithms throughout the processing line: from low to high level stages of analysis and content recognition. The existing architectures that we have described in the three first chapters of the thesis have shown their weaknesses that are expressed by reading errors and OCR rejections. The modules that are responsible of these rejections and reading errors are mostly the first to occur in the processes of image segmentation and interest regions location. Indeed, theses two processes, involving each other, are fundamental for the system performances and the efficiency of the automatic sorting lines. In this thesis, we have chosen to focus on different sides of mail images segmentation and of relevant zones (as address block) location. We have chosen to develop a model based on a new pyramidal approach using a hierarchical graph coloring. As for now, graph coloring has never been exploited in such context. It has been introduced in our contribution at every stage of document layout analysis for the recognition and decision tasks (kind of document or address block recognition). The recognition stage is made about a training process with a unique model of graph b-coloring. Our architecture is basically designed to guarantee a good cooperation bewtween the different modules of decision and analysis for the layout analysis and the recognition stages. It is composed of three main sections: the low-level segmentation (binarisation and connected component labeling), the physical layout extraction by hierarchical graph coloring and the address block location and document sorting. The algorithms involved in the system have been designed for their execution speed (matching with real time constraints), their robustness, and their compatibility. The experimentations made in this context are very encouraging and lead to investigate a wider diversity of document images.VILLEURBANNE-DOC'INSA-Bib. elec. (692669901) / SudocSudocFranceF

Text lines and snippets extraction for 19th century handwriting documents<br /> layout analysis

International audienceIn this paper we propose a new approach to improve electronic editions of human science corpus, providing an efficient estimation of manuscripts pages structure. In any handwriting documents analysis process, the text line segmentation is an important stage. The presence of variable inter-line spaces, of inconstant base-line skews, overlapping and occlusions in unconstrained ancient 19th handwritten documents complexifies the text lines segmentation task. In this paper, we only use as prior knowledge of script the fact that text lines skews can be random and irregular. In that context, we model text line detection as an image segmentation problem by enhancing text line structure using Hough transform and a clustering of connected components so as to make text line boundaries appear. The proposed approach of snippets decomposition for page layout analysis lies on a first step of content pages classification in five visual and genetic taxonomies, and a second step of text line extraction and snippets decomposition. Experiments show that the proposed method achieves high accuracy for detecting text lines in regular and semi-regular handwritten pages in the corpus of digitized Flaubert manuscripts ("Dossiers documentaires de Bouvard et Pécuchet", 1872-1880)

Hierarchical decomposition of handwritten<br /> manuscripts layouts

http://www.springerlink.com/content/k6741wt1028l7310/International audienceIn this paper we propose a new approach to improve electronic editions of literary corpus, providing an efficient estimation of manuscripts pages structure. In any handwriting documents analysis process, structure recognition is an important issue. The presence of variable inter-line spaces, of inconstant base-line skews, overlappings and occlusions in unconstrained ancient 19th handwritten documents complicates the structure recognition task. Text line and fragment extraction is basedon the connexity labelling of the adjacency graph at different resolutionlevels, for borders, lines and fragments extraction

La Numérisation et le catalogage des manuscrits

National audienc

Segmentation and Typography Extraction in Document Images Using Geodesic Active Regions

International audienceThis paper addresses the problem of typography extraction in document images. For that, we propose the use of robust textural image processing methods (Gabor filtering and the geodesic active regions model) instead of classical document image processing techniques (physical segmentation and logical labeling) which work at a pixel level and are very sensitive to a lot of parameters such as noise and skewing. We show, on a few examples, that our method is generic enough to cope with recurrent problems in the field of document processing

Font Type Extraction and Character Prototyping Using Gabor Filters.

International audienceIn this paper, we present an automatic method for character prototyping and font type characterization in machine-printed document images at a character level. To do so, we use a generic textural approach, which considers text as a texture, instead of working at a pixel level like most of the methods proposed so far. In this way, Gabor filtering seems to be an appropriate tool for texture characterization, since its design has been inspired by the human visual system. The objective of the paper is then to verify this hypothesis by applying our method on a corpus composed of what we call "typographically rich and recurrent" machine-printed document images

Contributions à l'indexation et à la reconnaissance des manuscrits syriaques

Cette thèse est dédiée à l exploration informatique de manuscrits syriaques, c est la première étude de ce type mise en œuvre. Le syriaque est une langue qui s est développé à l est du bassin méditerranéen, il y a plus de vingt siècles et qui aujourd hui est encore pratiquée. La présentation de l histoire du développement de cette langue fait l objet du premier chapitre. Le syriaque s écrit de droite à gauche, avec un aspect très singulier, un penché d un angle d environ 45 qui rend les algorithmes de traitement et d analyse de documents développés pour les autres écritures inopérants. Dans le second chapitre, après nous être intéressés à la description et l extraction des structures des documents, nous avons élaboré une méthode de segmentation des mots qui prend en compte ce penché ; elle nous conduit à une trentaine de formes stables qui sont des lettres individuelles verticales et des n-grammes constitués par des lettres penchées. Dans la deuxième partie de la thèse, nous nous sommes intéressés au contenu des documents à des fins d indexation. Nous avons développé une méthode de repérage de mots qui permet de retrouver, dans un document, toutes les occurrences d un mot selon plusieurs modes de requêtes (word spotting, word retrieval). Elle repose sur une similarité de forme évaluée à partir d une analyse très fine de l orientation du tracé de l écriture. Le dernier chapitre est une première contribution à la transcription assistée des manuscrits syriaques qui repose sur la segmentation des mots décrite ci-dessus. Nous montrons que la transcription, qui s appuie sur l interaction, est en rupture avec la traditionnelle démarche de reconnaissance par OCR.This thesis is dedicated to the computed exploration of Syriac manuscripts; it is the first study of the sort. Syriac is a language that developed in the eastern region of the Mediterranean coast, about twenty centuries ago, and is still in practice, today. The history as well as the development of the language is presented in the first chapter. Syriac is written from right to left with a distinct feature which is a tilt of about 45 which renders classical signal and document analysis algorithms which were developed for other languages rather useless. In the second chapter, after describing and extracting the documents structure, we developed a word segmentation method that takes this tilt into consideration, this lead us to about thirty stable shapes which are vertical letters and n-grammes made out of titled letters. In the second part of this thesis, we were interested in the content of the documents for indexation purposes. We developed a word spotting method that allowed us to find all the occurrences of a word in a document using several word query approaches (word spotting, word retrieval). It is based on shape similarity evaluated after a thorough analysis of the orientations of the handwriting. The last chapter consists of a first contribution to assisted transcription of Syriac manuscripts which relies on the above described segmentation. We showed that transcription based on interaction, is in conflict with the traditional approaches of OCR recognition.VILLEURBANNE-DOC'INSA LYON (692662301) / SudocSudocFranceF