Using a neighbourhood graph based on Voronoï tessellation with DMOS, a generic method for structured document recognition

To develop a method for structured document recognition, it is necessary to know the relative position of the graphical elements in a document. In order to deal with this notion, we build a neighbourhood graph based on Vorono¨ı tessellation. We propose to combine the use of this interesting notion of neighbourhood with an existing generic document recognition method, DMOS, which has been used to describe various kinds of documents. This association allows exploiting different aspects of the neighbourhood graph, separating the graph analysis from the knowledge linked to a kind of document, and establishing a bidirectional context-based relation between the analyser and the graph. We apply this method on the analysis of various documents

Un graphe de voisinage basé sur l'utilisation des distances discrètes

International audienceThe discrete distances are largely used in image processing : mathecatical morphology, fast extraction of skeleton, rebuilding... After an introduction, this paper presents in a first part (section 2), the principle of construction of a graph of vicinity between related components. This graph based on the use of the discrete distances, establishes a relation between the border points of each component, to allow a better knowledge of relative positionings of those components. This first part is based on a traditional implementation for the construction of the graph. The second part (section 3) of the paper proposes a particular implementation which allows a significant memory economy while extracting a graph. This graph although nonequivalent to section 2 graph, carries identical information (vicinity and distance). This graph makes it possible to answer the problem of relative positioning of the related components. Lastly, we will conclude by comparative assessment and some prospects.Les distances discrètes sont largement utilisées en traitement d'images : morphologie mathématique, extraction rapide de squelette, reconstruction... Après une introduction, cet article présente dans une première partie (section 2), le principe de construction d'un graphe de voisinage entre les composantes connexes d'une image. Ce graphe basé sur l'utilisation des distances discrètes, établit une relation entre les points contours de chacune des composantes, pour permettre une meilleure connaissance des positionnements relatifs des unes par rapport aux autres. Cette première partie s'appuie sur une implémentation classique pour la construction du graphe. La seconde partie (section 3) de l'article propose une implémentation particulière qui permet une économie mémoire importante tout en extrayant un graphe qui bien que non équivalent, porte des informations de même nature (voisinage et distance). Enfin, nous conclurons par un bilan comparatif entre les implémentations et par des perspectives d'utilisation d'un tel graph

Kalman Filter Contributions Towards Document Segmentation

International audienceOne way of tackling document analysis is to split the document into different layers and then find a segmentation for each one. The straight line is often one of the basic elements of the layers making a document. The dectection of these segments is often disturbed by the superposition of different layers in the same area. Therefore we developed a segment extractor, which processes masked areas, discontinuities ans even curvatures. After showing in our previous work, the interest of such a system in binary image analysis, our aim was to show the method could be generalized to grey level images, by taking into account pixel luminosity as one of the parameters. The Kalman filter method combined with an adequate control scheme, allows the pooling of local observations, when their position, width and luminosity are coherent. The proposed model gives an interesting scheme to manage drawings masking each other (eg. cross-lines).Une façon de s'attaquer à l'analyse de document consiste à séparer le document en différentes couches et ensuite de trouver une bonne segmentation pour chacune d'elles. Le trait droit est souvent un élément de base de ces couches qui composent les documents. La détection de ces segments est souvent perturbée par la superposition de différentes couches dans la même zone. C'est pourquoi nous avons développé un extracteur de segments, qui travaille avec les zones cachées, les discontinuités et même les courbures. Après avoir montré dans nos travaux précédents l'intérêt d'un tel syst1995ème pour l'analyse d'images binaires, notre but est de montrer que la méthode peut être généralisées aux images en niveaux de gris, en prenant en compte la luminosité des pixels comme l'un des paramètres. La méthode utilisant le filtre de Kalman combiné à un bon schéma de contrôle, autorise de passer en revue les observations locales, quand leurs position, épaisseur et luminosité sont cohérente. Le modèle proposé donne un schéma intéressant pour gérer les tracés qui se masquent les uns les autres (eg. les croisements)

Simple Monocular door detection and tracking

International audienceWhen considering an indoor navigation without using any prior knowledge of the environment, relevant landmark extraction remains an open issue for robot localization and navigation. In this paper, we consider indoor navigation along corridors. In such environments, when considering monocular cameras, doors can be seen as important landmarks. In this context, we present a new framework for door detection and tracking which exploits geometrical features of corridors. Since real-time properties are required for navigation purposes, designing solutions with a low computational complexity remains a relevant issue. The proposed algorithm relies on visual features such as lines and vanishing points that are further combined to discriminate the floor and wall planes and then to recognize doors within the image sequences. Detected doors are used to initialize a dedicated edge-based 2D door tracker. Experiments show that the framework is able to detect 82\% of doors on our dataset while respecting real time constraints

A Generic Recognition System for Making Archives Documents accessible to Public Bertrand Coasnon

This paper presents annotations needed for handwritten archives document retrieval by content. We propose two complementary ways of producing those annotations : automatically by using optical document recognition and collectively by using Internet and a manual input by users. A platform for managing those annotations is presented as well as examples of automatic annotations on civil status registers, military forms (tested on 60,000 pages) and naturalization decrees, using a generic document recognition method. Examples of collective annotations built on automatic annotations are also given

Une approche structurelle de la segmentation d'images et de la squelettisation

SIGLECNRS TD 15009 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Contribution d'une approche syntaxique dans la segmentation d'image

Disponible dans les fichiers attachés à ce documen

Simple Monocular door detection and tracking

International audienceWhen considering an indoor navigation without using any prior knowledge of the environment, relevant landmark extraction remains an open issue for robot localization and navigation. In this paper, we consider indoor navigation along corridors. In such environments, when considering monocular cameras, doors can be seen as important landmarks. In this context, we present a new framework for door detection and tracking which exploits geometrical features of corridors. Since real-time properties are required for navigation purposes, designing solutions with a low computational complexity remains a relevant issue. The proposed algorithm relies on visual features such as lines and vanishing points that are further combined to discriminate the floor and wall planes and then to recognize doors within the image sequences. Detected doors are used to initialize a dedicated edge-based 2D door tracker. Experiments show that the framework is able to detect 82\% of doors on our dataset while respecting real time constraints

Contribution d'une approche syntaxique dans la segmentation d'image

SIGLECNRS-CDST / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc