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Aug 06, 2007 at 11:09 PM

I've got a git where I put some of my developments.
Git: https://gitlab.com/romain.raveaux

  • Our methods have been implemented in python networkx : Website

  • C implementation of GED solvers here: Website

  • Learning error-correcting graph matching with a multiclass neural network : Website

  • Efficient k-nearest neighbors search in graph space : Website

  • New binary linear programming formulation to compute the graph edit distance : Website

  • Performance Evaluation : Snapshots
    • In this tool, we only consider the recognition precision of solid polygons. That is, although there are other classes of vectors, e.g , dashed lines, text, in both the ground truth file and the detected file, we only care about PMD and MED for ground truth solid polygons (i.e., PMD denotes how those ground truth solid polygons are detected?) (i.e., MED denotes how precise those detected solid polygons are?).
    • Polygon Matching Distance
    • A Cycle Graph Matching Distance for Polygon Comparison
    • The performance evaluation (PE) tool is available and can be downloaded at PE.jar. It is a JAVA application running on any systems. It accepts as input two vector files (the ground truth vector file and the detected vector file) in the SHAPE format defined by ESRI and outputs the PE results
    • A File : dist.csv containing all indices.
    • 2 Layers to visualize differences between the two vector files. (PMD and MED attributes on each polygon)
    • PMD : represesnts a polygon detection performance.
    • MED : defines a line detection performance evaluation protocol.
    • If you cannot run this PE tool, you can send me your ground truth file and detected file and I can run the tool on your files and send you back the PE result.
    • Executable can be downloaded here and run as "java -xmx512m -jar PE.jar"
    • Databases are avaiblable here

  • A Prototype Based Reduction Scheme for Structural Data Classification.
  • [PDF Presentation]

    This work was carried out in association with the LITIS lab at the university of Rouen. especially with Sebastien Adam and Pierre Héroux.
    • Symbol recognition based on a Graph classification
    • Genetic Algorithm using graph data structure
    • A fast dissimilarity measure between graphs called graph probing
    • K prototypes per class
    • From image of symbol to a graph representation using Statistical/Structural information.
    • .
    • Download and More information

  • A graph matching method based on probes assignments
  • This software aims at matching two attributed graphs. It runs fast O(n^3) and the univalent mapping can be expresssed as the minimum-weight probe matching between G1 and G2 Download and More information

    Image and Ontology

    Here are material I gave to Master degree students. This work is dealing with Image and Ontology. More precisely, how to classify regions of an image using an ontology reasoner.

  • Vectorial image segmentation and a graph based merging process.
  • This software performs two colour image segmentations. In addition, as a final stage an image vectorization algorithm is carried out. Concepts: Color gradient, statistical merging, neighborhood graph merging, raster image vectorization Download and More information

  • A Content Based Image Retrieval Method Using A Graph Representation.
  • Here, we propose an automatic system to annotating and retrieving images. We assume that regions in an image can be described using a small vocabulary of blobs. Blobs are generated from image features using clustering. Each image sees its blobs structured into a graph, a blob adjacency graph. This representation is used to perform a similarity search into an image set. Hence, the user can express his need by giving a query image, and thereafter receiving as a result all similar images. Download and More information

  • Best Colour Space Finder:
  • This software computes on a RGB image different feature selection methods in order to find the best colour space in term of data separability. Download and More information
    Last Updated ( Dec 13, 2019 at 03:20 PM )