TKDetection: a software to detect and segment wood knots

TKDetection is a software proposing to segment the wood knots obtained from X-Ray Computed Tomography (CT) scanners. It implements algorithms combining tools of image analysis and discrete geometry, like connected component extraction, contour extraction or dominant point detection. TKDetection is the first free and open source software for the automatic knot segmentation. It is available on Github platform

Recognition of Blurred Pieces of Discrete Planes

International audienceWe introduce a new discrete primitive, the blurred piece of a discrete plane, which relies on the arithmetic definition of discrete planes. It generalizes such planes, admitting that some points are missing and then permits to adapt to noisy discrete data. Two recognition algorithms of such primitives are proposed: the first one is a geometrical algorithm and minimizes the Euclidean distance and the second one relies on linear programming and minimizes the vertical distance

Multiorder polygonal approximation of digital curves

In this paper, we propose a quick threshold-free algorithm, which computes the angular shape of a 2D object from the points of its contour. For that, we have extended the method defined in [4, 5] to a multiorder analysis. It is based on the arithmetical definition of discrete lines [11] with variable thickness. We provide a framework to analyse a digital curve at different levels of thickness. The extremities of a segment provided at a high resolution are tracked at lower resolution in order to refine their location. The method is thresholdfree and automatically provides a partitioning of a digital curve into its meaningful parts

Segmentation of Noisy Discrete Surfaces

International audienceWe propose in this paper a segmentation process that can deal with noisy discrete objects. A flexible approach considering arithmetic discrete planes with a variable width is used to avoid the over-segmentation that might happen when classical segmentation algorithms based on regular discrete planes are used to decompose the surface of the object. A method to choose a seed and different segmentation strategies according to the shape of the surface are also proposed

3D Noisy Discrete Objects: Segmentation and Application to Smoothing

International audienceWe propose in this paper a segmentation process that can deal with noisy discrete objects. A flexible approach considering arithmetic discrete planes with a variable width is used to avoid the over-segmentation that might happen when classical segmentation algorithms based on regular discrete planes are used to decompose the surface of the object. A method to choose a seed and different segmentation strategies according to the shape of the surface are also proposed, as well as an application to smooth the border of convex noisy discrete objects

Decomposition of a curve into arcs and line segments based on dominant point detection

International audienceA new solution is proposed to decompose a curve into arcs and straight line segments in $O(n\log n)$ time. It is a combined solution based on arc detection \cite{Nguyen10a_} and dominant point detection \cite{Nguyen10f} to strengthen the quality of the segmentation results. Experimental results show the fastness of the proposed method

A discrete geometry approach for dominant point detection

International audienceWe propose two fast methods for dominant point detection and polygonal representation of noisy and possibly disconnected curves based on a study of the decomposition of the curve into the sequence of maximal blurred segments \cite{ND07}. Starting from results of discrete geometry \cite{FT99,Deb05}, the notion of maximal blurred segment of width $\nu$ \cite{ND07} has been proposed, well adapted to noisy curves. The first method uses a fixed parameter that is the width of considered maximal blurred segments. The second one is proposed based on a multi-width approach to obtain a non-parametric method that uses no threshold for working with noisy curves. Comparisons with other methods in the literature prove the efficiency of our approach. Thanks to a recent result \cite{FF08} concerning the construction of the sequence of maximal blurred segments, the complexity of the proposed methods is $O(n\log n)$. An application of vectorization is also given in this paper

Segmentation en arcs discrets en temps linéaire

Nous proposons un algorithme linéaire reposant sur une approche de géométrie discrète pour segmenter une courbe en arcs et cercles discrets. Cette méthode utilise une représentation originale des arcs et cercles discrets. En utilisant cette représentation, nous transformons le problème de reconnaissance d'arcs discrets en un problème de reconnaissance de droites discrètes et nous en déduisons un algorithme de segmentation

Fast and robust dominant point detection on digital curves

International audienceA new and fast method for dominant point detection and polygonal representation of a discrete curve is proposed. Starting from results of discrete geometry, the notion of maximal blurred segment of width v has been proposed, well adapted to possibly noisy and/or not connected curves. For a given width, the dominant points of a curve C are deduced from the sequence of maximal blurred segments of C in O(nlog^2n) time. Comparisons with other methods of the literature prove the efficiency of our approach

A multiscale approach to decompose a digital curve into meaningful parts

International audienceA multi-scale approach is proposed for polygonal repre- sentation of a digital curve by using the notion of blurred seg- ment and a split-and-merge strategy. Its main idea is to de- compose the curve into meaningful parts that are represented by detected dominant points at the appropriate scale. The method uses no threshold and can automatically decompose the curve into meaningful parts