Jean-Philippe Domenger

BUBBLE TREE DRAWING ALGORITHM

In this paper, we present an algorithm, called Bubble Tree, for the drawing of general rooted trees. A large variety of algorithms already exists in this field. However, the goal of this algorithm is to obtain a better drawing which makes a trade off between the angular resolution and the length of the edges. We show that the Bubble Tree drawing algorithm provides a planar drawing with at most one bend per edge in linear running time.

Propagation beam consideration for 3D THz computed tomography

In this paper, a model of the beam propagation is developed according to the physical properties of THz waves used in THz computed tomography (CT) scan imaging. This model is first included in an acquisition simulator to observe and estimate the impact of the Gaussian beam intensity profile on the projection sets. Second, the model is introduced in several inversion methods as a convolution filter to perform efficient tomographic reconstructions of simulated and real acquired objects. Results obtained with three reconstruction methods (BFP, SART and OSEM) are compared to the techniques proposed in this paper. We will demonstrate an increase of the overall quality and accuracy of the 3D reconstructions.

Retrieval of objects in video by similarity based on graph matching

In this paper, we tackle the problem of matching of objects in video in the context of the rough indexing paradigm. The approach developed is based on matching of region adjacency graphs (RAG) of pre-segmented objects. In the context of the rough indexing paradigm, the video data are of very low resolution and segmentation is consequently inaccurate. Hence the RAGs vary with the time. The contribution of this paper is a graph matching method for such RAGs based on an improvement of relaxation labelling techniques. In this method, adjustments of similarity between regions according to neighborhood consistency compensate for the inaccuracy of segmentation. The approach demonstrates promising performance on real sequences when compared to another region-based technique.

Segmentation-based multi-class semantic object detection

In this paper we study the problem of the detection of semantic objects from known categories in images. Unlike existing techniques which operate at the pixel or at a patch level for recognition, we propose to rely on the categorization of image segments. Recent work has highlighted that image segments provide a sound support for visual object class recognition. In this work, we use image segments as primitives to extract robust features and train detection models for a predefined set of categories. Several segmentation algorithms are benchmarked and their performances for segment recognition are compared. We then propose two methods for enhancing the segments classification, one based on the fusion of the classification results obtained with the different segmentations, the other one based on the optimization of the global labelling by correcting local ambiguities between neighbor segments. We use as a benchmark the Microsoft MSRC-21 image database and show that our method competes with the current state-of-the-art.

Discrete Maps: a Framework for Region Segmentation Algorithms

In this paper, we present different recent segmentation works based on discrete maps. Discrete maps provide an efficient framework for region based segmentation methods. A discrete map is a mixed model combining an encoding of the discrete boundaries of the image regions with topological graphs which represent the topology of the image.

New Strahler numbers for rooted plane trees

In this paper, wepresent an extension of Strahler numbers to rooted plane trees. Several asymptotic properties are proved; others are conjectured. We also describe several applications of this extension.

Efficient drawing of RNA secondary structure

In this paper, we propose a new layout algorithm that draws the secondary structure of a Ribonucleic Acid (RNA) automatically according to some of the biologists’ aesthetic criteria. Such layout insures that two equivalent structures (or sub-structures) are drawn in a same and planar way. In order to allow a visual comparison of two RNAs, we use an heuristic that places the biggest similar part of the two structures in the same position and orientation.

Content based image retrieval using bag-of-regions

In this work we introduce the Bag-Of-Regions model, inspired from the Bag-Of-Visual-Words. Instead of clustering local image patches represented by SIFT or related descriptors, low level descriptors are extracted and clustered from image regions, as given by a segmentation algorithm. The Bag-Of-Region model allows to define visual dictionaries that capture extra information with respect to Bag-Of-Visual-Words. Combined description schemes and ad-hoc incremental clustering for visual dictionnaries are proposed. The results on public datasets are promising.

Terahertz radiation for tomographic inspection

Abstract. Three-dimensional (3-D) terahertz computed tomography has already been performed with three different reconstruction methods (standard back-projection algorithm and two iterative analyses) to reconstruct 3-D objects. A Gaussian beam model is developed according to the physical properties of terahertz waves such as the energy distribution within the propagation path. This model is included as a new convolution filter into the tomographic reconstruction methods in order to analyze the impact of a such effect and then to enhance quality and accuracy of the resulting images. We demonstrate the improvements of the optimized reconstructions for applied 3-D terahertz tomography.

Incremental modifications of segmented image defined by discrete maps

Abstract The data structure used to encode an image partition is of critical importance for most of region-based segmentation algorithms. Usual data structures are often convenient to extract only few parameters from the partition while inducing complex processing to compute others. Moreover, the split and merge operations allowed by such data structure are often restricted. A new model ( Braquelaire and Brun, 1998 ) based on discrete maps allows segmentation algorithms to perform unrestricted split and merge operations and extract a wide range of parameters from a partition. In this paper we describe the two basic primitives used by segmentation algorithms to modify a partition: the segment insertion and segment suppression.