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- Sébastien Macé, Hervé Locteau, Ernest Valveny, Salvatore Tabbone
- Document Analysis Systems
- 2010

In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical… (More)

In this paper, we tackle the problem of localizing graphical symbols on complex technical document images by using an original approach to solve the subgraph isomorphism problem. In the proposed system, document and symbol images are represented by vector-attributed Region Adjacency Graphs (RAG) which are extracted by a segmentation process and feature… (More)

In this paper we present a system to build synthetic graphical documents for the performance evaluation of symbol recognition systems. The key contribution of this work is the building of whole document like drawings or maps. We exploit the layer property of graphical documents by putting symbol sets in different ways from a same background using… (More)

In this paper, a method for matching symbols in line-drawings is presented. Facing both segmentation and recognition of symbols is a difficult challenge. Starting from the results of a vectorization procedure, a visibility graph is built to enhance the main geometric constraints which were specified during the construction of the initial document. The… (More)

We present in this paper a graph classification approach using genetic algorithm and a fast dissimilarity measure between graphs called graph probing. The approach consists in the learning of a set of synthetic graph prototypes which are used for a 1NN classification step. Some experiments are performed on real data sets, representing 10 symbols. These… (More)

- Romain Raveaux, Eugen Barbu, Hervé Locteau, Sébastien Adam, Pierre Héroux, Éric Trupin
- GbRPR
- 2007

In this paper, a graph classification approach based on a multiobjective genetic algorithm is presented. The method consists in the learning of sets composed of synthetic graph prototypes which are used for a classification step. These learning graphs are generated by simultaneously maximizing the recognition rate while minimizing the confusion rate. Using… (More)

In this paper, a digital planar curve approximation method based on a multi-objective genetic algorithm is proposed. In this method, the optimization/exploration algorithm locates breakpoints on the digital curve by minimizing simultaneously the number of breakpoints and the approximation error. Using such an approach, the algorithm proposes a set of… (More)

In this paper, a polygonal approximation approach based on a multiobjective genetic algorithm is proposed. In this method, the optimization/exploration algorithm locates breakpoints on the digital curve by minimizing simultaneously the number of breakpoints and the approximation error. Using such an approach, the algorithm proposes a set of solutions at its… (More)

In this paper we present a system to build synthetic graphic documents for performance evaluation using two main components. The first one performs a vectorial distortion on the objects without using any prior knowledge. The other position the objects in the documents using four filling algorithms allowing to preserve a partitioning between the objects and… (More)

In this paper, we investigates symbol representation introducing a new hybrid approach. Using a combination of statistical and structural descriptors, we overcome deficiencies of each method taken alone. Indeed, a Region Adjacency Graph of loops is associated with a graph of vectorial primitives. Thus, a loop is both representend in terms of its boundaries… (More)

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