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  • 1.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Norell, Kristin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Wadelius, Lena
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Annual Report 20072008Report (Other (popular science, discussion, etc.))
  • 2.
    Norell, Kristin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    An automatic method for counting annual rings in noisy sawmill images2009In: Image Analysis and Processing – ICIAP 2009, Springer Berlin / Heidelberg , 2009, p. 307-316Conference paper (Refereed)
    Abstract [en]

    The annual ring pattern of a log end face is related to the quality of the wood. We propose a method for computing the number of annual rings on a log end face depicted in sawmill production. The method is based on the grey-weighted polar distance transform and registration of detected rings from two different directions. The method is developed and evaluated on noisy images captured in on-line sawmill production at a Swedish sawmill during 2008, using an industrial colour camera. We have also evaluated the method using synthetic data with different ring widths, ring eccentricity, and noise levels.

  • 3.
    Norell, Kristin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Automatic counting of annual rings on Pinus sylvestris end faces in sawmill industry2011In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 75, no 2, p. 231-237Article in journal (Refereed)
  • 4.
    Norell, Kristin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Creating synthetic log end face images2009In: Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009.: ISPA 2009. / [ed] P. Zinterhof; S. Loncaric; A. Uhl; A.Carini, 2009, p. 353-358Conference paper (Refereed)
    Abstract [en]

    In this paper we present the design and creation of synthetic images of log end faces. The images are constructed to resemble images of Scots pine taken in on-line sawmill production. Wood features such as knots, heartwood, and annual rings, as well as the sawing procedure, storage, and imaging, including camera position, are simulated. A dataset of 100 images is provided, together with code for generating new synthetic data.

  • 5.
    Norell, Kristin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Estimation of pith position in untreated log ends in sawmill environments2008In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 63, no 2, p. 155-167Article in journal (Refereed)
    Abstract [en]

    Two related methods for automatic estimation of the pith position, i.e., the centre of the annual rings, in wood log end face images are presented. We use images that depict untreated log end faces that are deliberately chosen to include difficulties such as rot, non-circular shape, uncentered pith and dirt. The images are taken with a regular digital camera in sawmill environments. Both presented methods use local orientation and Hough transform to detect the pith position, but two different ways to compute the local orientation are used. The results are promising for both methods. At least one of the methods is fast enough to use on-line at a sawmill.

  • 6.
    Norell, Kristin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Spatially-variant morphological operations on binary images based on the polar distance transform2008In: ICPR 2008, IEEE computer society , 2008Conference paper (Refereed)
    Abstract [en]

    Binary mathematical morphology can be computed by thresholding a distance transform, provided that the distance transform is a metric. Here we show that the polar distance transform is a metric and use it for morphological operations. The polar distance transform varies with the spatial coordinates of the image, resulting in spatially-variant morphology. In this distance transform each pixel is related to an image origin. We prefer angular propagation over radial, thus we construct structuring elements that are elongated in the angular direction, which is useful when circular segments are handled. We show an example where segments of annual rings on a log end face are connected using mathematical morphology based on the polar distance transform.

  • 7.
    Norell, Kristin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Grey Weighted Polar Distance Transform for Outlining Circular and Approximately Circular Objects2007In: 14th International Conference on Image Analysis and Processing: ICIAP 2007, 2007, p. 647-652Conference paper (Refereed)
    Abstract [en]

    We introduce the polar distance transform and the grey weighted polar distance transform for computation of minimum cost paths preferring circular shape, as well as give algorithms for implementations in a digital setting. An alternative to the polar distance transform is to transform the image to polar coordinates, and then apply a Cartesian distance transform. By using the polar distance transform, re-sampling of the image and interpolation of new pixel values are avoided. We also handle the case of grey weighted distance transform in a $5\times 5$ neighbourhood, which, to our knowledge, is new. Initial results of using the grey weighted polar distance transform to outline annual rings in images of log end faces are presented.

  • 8.
    Norell, Kristin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    The polar distance transform2008In: Proceedings SSBA 2008, Symposium on image analysis, Lund, 2008Conference paper (Other academic)
    Abstract
1 - 8 of 8
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