378 research outputs found

    TKDetection: a software to detect and segment wood knots

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    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

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    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

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    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

    Acquis et limites de l’hormonothérapie adjuvante

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    Neoadjuvant endocrine treatment

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    Musculoskeletal symptoms after breast cancer treatments

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    Revisiting Digital Straight Segment Recognition

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    This paper presents new results about digital straight segments, their recognition and related properties. They come from the study of the arithmetically based recognition algorithm proposed by I. Debled-Rennesson and J.-P. Reveill\`es in 1995 [Debled95]. We indeed exhibit the relations describing the possible changes in the parameters of the digital straight segment under investigation. This description is achieved by considering new parameters on digital segments: instead of their arithmetic description, we examine the parameters related to their combinatoric description. As a result we have a better understanding of their evolution during recognition and analytical formulas to compute them. We also show how this evolution can be projected onto the Stern-Brocot tree. These new relations have interesting consequences on the geometry of digital curves. We show how they can for instance be used to bound the slope difference between consecutive maximal segments

    Segmentation of Noisy Discrete Surfaces

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    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

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

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    International audienceA new solution is proposed to decompose a curve into arcs and straight line segments in O(nlogn)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

    3D Noisy Discrete Objects: Segmentation and Application to Smoothing

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    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
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