Edwin Carlinet

In PLOS ONE

Abstract Shape vectorization is a key stage of the digitization of large-scale historical maps, especially city maps that exhibit complex and valuable details. Having access to digitized buildings, building blocks, street networks and other geographic content opens numerous new approaches for historical studies such as change tracking, morphological analysis and density estimations. In the context of the digitization of Paris atlases created in the 19th and early 20th centuries, we have designed a supervised pipeline that reliably extract closed shapes from historical maps.

Création d’un graphe de connaissances géohistorique à partir d’annuaires du commerce parisien du 19 ème siècle: Application aux métiers de la photographie

By Solenn Tual, Nathalie Abadie, Bertrand Duménieu, Jospeh Chazalon, Edwin Carlinet

2023-07-01

In 34es Journées francophones d’Ingénierie des Connaissances (IC 2023) @ Plate-Forme Intelligence Artificielle (PFIA 2023)

Abstract Les annuaires professionnels anciens, édités à un rythme soutenu dans de nombreuses villes européennes tout au long des XIXe et XXe si‘ecles, forment un corpus de sources unique par son volume et la possibilité qu’ils donnent de suivre les transformations urbaines à travers le prisme des activités professionnelles des habitants, de l’échelle individuelle jusqu’à celle de la ville enti‘ere. L’analyse spatiotemporelle d’un type de commerces au travers des entrées d’annuaires demande cependant un travail considérable de recensement, de transcription et de recoupement manuels.

Structural analysis of the additive noise impact on the $\alpha$-tree

By Baptiste Esteban, Guillaume Tochon, Edwin Carlinet, Didier Verna

2023-06-30

In Proceedings of the 20th international conference on computer analysis of images and patterns (CAIP)

Abstract Hierarchical representations are very convenient tools when working with images. Among them, the $\alpha$-tree is the basis of several powerful hierarchies used for various applications such as image simplifi- cation, object detection, or segmentation. However, it has been demon- strated that these tasks are very sensitive to the noise corrupting the image. While the quality of some $\alpha$-tree applications has been studied, including some with noisy images, the noise impact on the whole struc- ture has been little investigated.

A benchmark of nested named entity recognition approaches in historical structured documents

By Solenn Tual, Nathalie Abadie, Joseph Chazalon, Bertrand Duménieu, Edwin Carlinet

2023-06-01

In Proceedings of the international conference on document analysis and recognition (ICDAR 2023)

Abstract Named Entity Recognition (NER) is a key step in the creation of structured data from digitised historical documents. Traditional NER approaches deal with flat named entities, whereas entities are often nested. For example, a postal address might contain a street name and a number. This work compares three nested NER approaches, including two state-of-the-art approaches using Transformer-based architectures. We introduce a new Transformer-based approach based on joint labelling and semantic weighting of errors, evaluated on a collection of 19th-century Paris trade directories.

Linear object detection in document images using multiple object tracking

By Philippe Bernet, Joseph Chazalon, Edwin Carlinet, Alexandre Bourquelot, Élodie Puybareau

2023-06-01

In Proceedings of the international conference on document analysis and recognition (ICDAR 2023)

Abstract Linear objects convey substantial information about document structure, but are challenging to detect accurately because of degradation (curved, erased) or decoration (doubled, dashed). Many approaches can recover some vector representation, but only one closed-source technique introduced in 1994, based on Kalman filters (a particular case of Multiple Object Tracking algorithm), can perform a pixel-accurate instance segmentation of linear objects and enable to selectively remove them from the original image. We aim at re-popularizing this approach and propose: 1.

The Dahu graph-cut for interactive segmentation on 2D/3D images

By Minh Ôn Vũ Ngọc, Edwin Carlinet, Jonathan Fabrizio, Thierry Géraud

2022-12-03

In Pattern Recognition

Abstract Interactive image segmentation is an important application in computer vision for selecting objects of interest in images. Several interactive segmentation methods are based on distance transform algorithms. However, the most known distance transform, geodesic distance, is sensitive to noise in the image and to seed placement. Recently, the Dahu pseudo-distance, a continuous version of the minimum barrier distance (MBD), is proved to be more powerful than the geodesic distance in noisy and blurred images.

A modern C++ point of <i>view</i> of programming in image processing

By Michaël Roynard, Edwin Carlinet, Thierry Géraud

2022-10-10

In Proceedings of the 21st international conference on generative programming: Concepts & experiences (GPCE 2022)

Abstract C++ is a multi-paradigm language that enables the programmer to set up efficient image processing algorithms easily. This language strength comes from many aspects. C++ is high-level, so this enables developing powerful abstractions and mixing different programming styles to ease the development. At the same time, C++ is low-level and can fully take advantage of the hardware to deliver the best performance. It is also very portable and highly compatible which allows algorithms to be called from high-level, fast-prototyping languages such as Python or Matlab.

The cost of dynamism in static languages for image processing

By Baptiste Esteban, Edwin Carlinet, Guillaume Tochon, Didier Verna

2022-10-10

In Proceedings of the 21st international conference on generative programming: Concepts & experiences (GPCE 2022)

Abstract Generic programming is a powerful paradigm abstracting data structures and algorithms to improve their reusability, as long as they respect a given interface. Coupled with a performance-driven language, it is a paradigm of choice for scientific libraries where the implementation of manipulated objects may change depending on their use case, or for performance purposes. In those performance-driven languages, genericity is often implemented statically to perform some optimization. This does not fit well with the dynamism needed to handle objects which may only be known at runtime.

Estimation de la fonction de niveau de bruit pour des images couleurs en utilisant la morphologie mathématique

By Baptiste Esteban, Guillaume Tochon, Edwin Carlinet, Didier Verna

2022-06-15

In 28e colloque sur le traitement du signal et des images

Abstract Le niveau de bruit est une information importante pour certaines applications de traitement d’image telles que la segmentation ou le débruitage. Par le passé, nous avons proposé une méthode pour estimer ce niveau de bruit en s’adaptant au contenu d’une image en niveau de gris et nous avons montré que ses performances dépassent celle de l’état de l’art. Dans cet article, nous proposons une extension de cette méthode aux images couleurs dont les valeurs multivariées, dénuées de relation d’ordre naturelle, impliquent de nouvelles problématiques.

Généricité dynamique pour des algorithmes morphologiques

By Baptiste Esteban, Edwin Carlinet, Guillaume Tochon, Didier Verna

2022-06-15

In 28e colloque sur le traitement du signal et des images

Abstract La généricité est un paradigme puissant dont l’usage permet d’implémenter un unique algorithme et de l’exécuter sur différents types de données. De ce fait, il est très utilisé lors du développement d’une bibliothèque scientifique, notamment en traitement d’images où les algorithmes peuvent s’appliquer à différents types d’images. Le langage C++ est un langage de choix pour ce genre de bibliothèque. Il supporte ce paradigme et ses applications sont performantes compte tenu de sa nature compilée.

Automatic vectorization of historical maps: A benchmark

Création d’un graphe de connaissances géohistorique à partir d’annuaires du commerce parisien du 19 ème siècle: Application aux métiers de la photographie

Structural analysis of the additive noise impact on the $\alpha$-tree

A benchmark of nested named entity recognition approaches in historical structured documents

Linear object detection in document images using multiple object tracking

The Dahu graph-cut for interactive segmentation on 2D/3D images

A modern C++ point of <i>view</i> of programming in image processing

The cost of dynamism in static languages for image processing

Estimation de la fonction de niveau de bruit pour des images couleurs en utilisant la morphologie mathématique

Généricité dynamique pour des algorithmes morphologiques

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