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1.

Axelsson, Maria

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.

Segmentation of individual fibres in volume images is important when analysing the three dimensional (3D) fibre structure in paper and cellulose based composite materials. This paper presents a novel method for 3D tracking of individual fibres which can be used as a pre-segmentation step to a full cell wall segmentation or be used to estimate the fibre orientation. The tracking starts in one seed in each fibre and automatically extracts the local fibre orientation and the fibre centre point in each step using 3D information. Good results are obtained for cellulose fibres that are partially collapsed, cracked or irregularly shaped. The proposed method can also be used in other applications where tracking of tubular structures is of interest.

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.

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.

Chinga, Gary

Svensson, Stina

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Nygård, Per

Malmberg, Filip

Solheim, Olav

Lindblad, Joakim

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Borgefors, Gunilla

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.

Sintorn, Ida-Maria

Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.

Svensson, Stina

Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.

Borgefors, Gunilla

Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.

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.

Svensson, Stina

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Borgefors, Gunilla

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Ring artifacts can occur in reconstructed images from X-ray microtomography as full or partial circles centred on the rotation axis. In this paper, a 2D method is proposed that reduces these ring artifacts in the reconstructed images. The method consists of two main parts. First, the artifacts are localised in the image using local orientation estimation of the image structures and filtering to find ring patterns in the orientation information. Second, the map of the located artifacts is used to calculate a correction image using normalised convolution. The method is evaluated on 2D images from volume data of paper fibre imaged at the European Synchrotron Radiation Facility (ESRF) with high resolution X-ray microtomography. The results show that the proposed method reduces the artifacts and restores the pixel values for all types of partial and complete ring artifacts where the signal is not completely saturated.

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.

Östlund, Catherine

Vomhoff, Hannes

Svensson, Stina

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

A method for determining the water content at the interface between a press felt and a paper web has been developed. The water content was obtained by subtracting the estimated volume of the indented fibre web from the measured felt surface porosity of the press felt. The felt surface porosity was calculated from a topography map that was imaged with a Confocal Laser Scanning Microscope (CLSM) method. Here, the press felt was compressed against a smooth surface using a stress in the range of 0 to 10 MPa. Artefacts in the CLSM images were reduced using an image analysis method. The indentation of paper webs into the measured felt surface pores at different applied pressures was estimated using another image analysis method, simulating a rolling ball, with different radii of curvature for the different pressures and grammages, rolling over the felt surface. The ball radii were determined for a low and a high grammage web using the STFI-Packforsk Dewatering model. The method was evaluated in a case study with four press felts that had batt fibre diameters in a range between 22 and 78 μm. The indentation was calculated for webs with a low (15 g/m2) and a high grammage (105 g/m2), respectively. The evaluation showed that a considerable amount of porespace is available at the interface between the web and the felt. In most cases, the volume of the water-filled pores accounted for approximately 50% of the total surface porosity of the felt. Assuming a complete water saturation of the web/felt interface, approximately 10 g/m2 of water for the finest felt surface up to 40 g/m2 for the coarsest felt surface, could be located at the interface between the press felt and the paper web at a load of 10 MPa. This implies that a considerable amount of water is available for separation rewetting.

8.

Axelsson, Maria

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.

Östlund, Catherine

Vomhoff, Hannes

Svensson, Stina

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, 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.

Axelsson, Maria

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.

Borgefors, Gunilla

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, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.

Svensson, Stina

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Malmberg, Filip

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.

Borgefors, Gunilla

Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.