Adrien Krähenbühl

Adrien Krähenbühl
University of Strasbourg | UNISTRA · Institut universitaire de technologie Robert Schuman

Ph.D.

About

24
Publications
4,969
Reads
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231
Citations
Citations since 2016
10 Research Items
145 Citations
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
Introduction
Additional affiliations
September 2017 - present
University of Strasbourg
Position
  • Research Associate
September 2015 - August 2017
University of Bordeaux
Position
  • PostDoc
September 2015 - present
University of Bordeaux
Position
  • Research Assistant
Education
September 2009 - September 2011
University of Lorraine
Field of study
  • Computer Science
September 2005 - June 2009
University of Lorraine
Field of study
  • Mathematics - Computer science

Publications

Publications (24)
Book
This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on Reproducible Research in Pattern Recognition, RRPR 2021, held as a virtual event, in January 2021. The 8 revised full papers, presented together with 6 short papers, were carefully reviewed and selected from 18 submissions. The papers were...
Chapter
There exist several dissemination repositories, computation platforms, and online tools that might be used to implement Reproducible Research. In this paper, we discuss the strengths and weaknesses, or better, the adequacy of each of them for this purpose. Specifically, we present aspects such as the freely availability of contents for the scientif...
Poster
Full-text available
The paper presents how we designed a specific way to use the SIFT descriptor to estimate the landmarks in biological images.
Conference Paper
Full-text available
This paper focuses on the implementation details of a recent method which extracts the centerline of 3D shapes using solely partial mesh scans of these shapes. This method [9] extracts the shape centerline by constructing an accumulation map from input points and normal vectors and by filtering it with a confidence vote. This paper presents in deta...
Conference Paper
This paper proposes a fast, accurate and automatic method to segment wood knots from images obtained by X-Ray Computed Tomography scanner. The wood knot segmentation is a classical problem where the most popular segmentation techniques produce unsatisfactory results. In a previous work, a method was developed to detect knot areas and an approach wa...
Conference Paper
Full-text available
This paper proposes to improve the approach presented in Krähenbühl et al. [11] to build automatic methods for the wood knot detection from X-Ray CT scanner images. The major drawbacks of the previous method mostly depends on the variety of the distribution of knots and their geometric shapes. Our aim is to extend the robustness by performing the a...
Conference Paper
Full-text available
This paper proposes a simple and efficient method for the reconstruction and extraction of geometric parameters from 3D tubular objects. Our method constructs an image that accumulates surface normal information, then peaks within this image are located by tracking. Finally, the positions of these are optimized to lie precisely on the tubular shape...
Thesis
Full-text available
L'étude non destructive du bois à partir de scanners à rayons X nécessite d’imaginer de nouvelles solutions adaptées à l'analyse des images. Préoccupation à la fois de la recherche agronomique et du milieu industriel des scieries, la segmentation des nœuds de bois est un défi majeur en termes de robustesse aux spécificités de chaque espèce et aux c...
Thesis
Full-text available
L’étude non destructive du bois à partir de scanners à rayons X nécessite d’imaginer de nouvelles solutions adaptées à l’analyse des images. Préoccupation à la fois de la recherche agronomique et du milieu industriel des scieries, la segmentation des nœuds de bois est un défi majeur en termes de robustesse aux spécificités de chaque espèce et aux c...
Article
Abstract This paper proposes a fully automatic method to segment wood knots from images obtained by an X-ray Computed Tomography scanner. Wood knot segmentation is known to be a difficult problem in the presence of sapwood because of the quite similar density of knots and wet sapwood. Classical segmentation techniques produce unsatisfactory results...
Conference Paper
Full-text available
Segmentation de noeuds de bois à partir d'images tomodensitométriques : approches transversales et tangentielles Résumé Le traitement automatique des images tomodensitométriques de bois doit permettre aux scieries d'optimiser le rendement et la qualité des planches. Les noeuds de bois sont le principal facteur de qualité d'une planche et déterminer...
Conference Paper
Full-text available
Cet article présente une méthode rapide, précise et automatique pour segmenter les nœuds de bois à partir d’images volumiques de troncs d’arbres obtenues par scanner à rayons X. La segmentation des nœuds est un problème récurrent où les techniques classiques produisent des résultats non satisfaisants. Un premier travail nous a permis de développer...
Article
Computed Tomography (CT) is more and more used in forestry science and wood industry to explore internal tree stem structure in a non-destructive way. Automatic knot detection and segmentation in the presence of wet areas like sapwood for softwood species is a recurrent problem in the literature. This article describes an algorithm named TEKA able...
Conference Paper
Full-text available
Resolving a 3D segmentation problem is a common challenge in the domain of digital medical imaging. In this work, we focus on another original application domain: the 3D images of wood stem. At first sight, the nature of wood image looks easier to segment than classical medical image. However, the presence in the wood of a wet area called sapwood r...
Article
Full-text available
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 aut...
Conference Paper
Full-text available
This paper presents an original problem of knot detection in 3D X-ray Computer Tomography images of wood stems. This image type is very different from classical medical images and presents specific geometric structures. These ones are characteristic of wood stems na-ture. The contribution of this work is to exploit the original geometric structures...
Conference Paper
This paper presents an original problem of knot detection in 3D X-ray Computer Tomography images of wood stems. This image type is very different from classical medical images and presents specific geometric structures. These ones are characteristic of wood stems nature. The contribution of this work is to exploit the original geometric structures...
Conference Paper
Full-text available
X-ray computer tomography (CT) is the most promising method for non-destructively analysing knottiness in wood logs or beams. Two methods for measuring knot size and location from stacks of CT-images were developed and applied to a wide range of wood samples. The first method aims to provide exhaustive and accurate measurements by manually pointing...
Article
An algorithm to automatically detect and measure knots in CT images of softwood beams was developed. The algorithm is based on the use of 3D connex components and a 3D distance transform constituting a new approach for knot diameter measurements. The present work was undertaken with the objective to automatically and non-destructively extract the d...

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