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Borgefors, Gunilla
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Publications (10 of 52) Show all publications
Borgefors, G. (2018). The Scarcity of Universal Colour Names. In: Maria de Marisco, Gabriella Sannniti di Baja, Ana Fred (Ed.), Proceedings of 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018): . Paper presented at 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018), Madeira, Portugal, Jan 16-18, 2018. (pp. 496-502). SciTePress
Open this publication in new window or tab >>The Scarcity of Universal Colour Names
2018 (English)In: Proceedings of 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018) / [ed] Maria de Marisco, Gabriella Sannniti di Baja, Ana Fred, SciTePress, 2018, p. 496-502Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

There is a trend in Computer Vision to use over twenty colour names for image annotation, retrieval and to train deep learning networks to name unknown colours for human use. This paper will show that there is little consistency of colour naming between languages and even between individuals speaking the same language. Experiments will be cited that show that your mother tongue influences how your brain processes colour. It will also be pointed out that the eleven so called basic colours in English are not universal and cannot be applied to other languages. The conclusion is that only the six Hering primary colours, possibly with simple qualifications, are the only ones you should use if you aim for universal usage of your systems. That is: black, white, red, green, blue, and yellow.

Place, publisher, year, edition, pages
SciTePress, 2018
Keywords
Colour Names, Basic Colour Terms, Colour Perception, Deep learning, Image Retrieval, Image annotation
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-339659 (URN)10.5220/0006649004960502 (DOI)000447747100058 ()978-989-758-276-9 (ISBN)
Conference
7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018), Madeira, Portugal, Jan 16-18, 2018.
Available from: 2018-01-22 Created: 2018-01-22 Last updated: 2018-12-17Bibliographically approved
Saha, P. K., Borgefors, G. & Sanniti di Baja, G. (2017). Skeletonization and its applications – a review. In: Skeletonization: Theory, Methods, and Applications (pp. 3-42). London: Academic Press
Open this publication in new window or tab >>Skeletonization and its applications – a review
2017 (English)In: Skeletonization: Theory, Methods, and Applications, London: Academic Press, 2017, p. 3-42Chapter in book (Refereed)
Place, publisher, year, edition, pages
London: Academic Press, 2017
Series
Computer Vision and Pattern Recognition
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-325859 (URN)10.1016/B978-0-08-101291-8.00002-X (DOI)978-0-08-101291-8 (ISBN)
Available from: 2017-06-09 Created: 2017-06-28 Last updated: 2018-01-13Bibliographically approved
Saha, P. K., Borgefors, G. & Sanniti di Baja, G. (Eds.). (2017). Skeletonization: Theory, Methods, and Applications. London: Academic Press
Open this publication in new window or tab >>Skeletonization: Theory, Methods, and Applications
2017 (English)Collection (editor) (Refereed)
Place, publisher, year, edition, pages
London: Academic Press, 2017
Series
Computer Vision and Pattern Recognition
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-325864 (URN)10.1016/B978-0-08-101291-8.00017-1 (DOI)978-0-08-101291-8 (ISBN)
Available from: 2017-06-09 Created: 2017-06-28 Last updated: 2018-01-13Bibliographically approved
Saha, P. K., Borgefors, G. & Sanniti di Baja, G. (2016). A survey on skeletonization algorithms and their applications. Pattern Recognition Letters, 76, 3-12
Open this publication in new window or tab >>A survey on skeletonization algorithms and their applications
2016 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 76, p. 3-12Article in journal (Refereed) Published
Abstract [en]

Skeletonization provides an effective and compact representation of objects, which is useful for object description, retrieval, manipulation, matching, registration, tracking, recognition, and compression. It also facilitates efficient assessment of local object properties, e.g., scale, orientation, topology, etc. Several computational approaches are available in literature toward extracting the skeleton of an object, some of which are widely different in terms of their principles. In this paper, we present a comprehensive and concise survey of different skeletonization algorithms and discuss their principles, challenges, and benefits. Topology preservation, parallelization, and multi-scale skeletonization approaches are discussed. Finally, various applications of skeletonization are reviewed and the fundamental challenges of assessing the performance of different skeletonization algorithms are discussed.

Keywords
Skeletonization, Centers of maximal balls, Distance transform, Topology preservation, Parallel algorithms, Applications
National Category
Discrete Mathematics
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-266313 (URN)10.1016/j.patrec.2015.04.006 (DOI)000375135600002 ()
Available from: 2015-04-28 Created: 2015-11-06 Last updated: 2017-12-01Bibliographically approved
Saha, P. K., Strand, R. & Borgefors, G. (2015). Digital topology and geometry in medical image processing: A survey. IEEE Transactions on Medical Imaging, 34(9), 1940-1964
Open this publication in new window or tab >>Digital topology and geometry in medical image processing: A survey
2015 (English)In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 34, no 9, p. 1940-1964Article in journal (Refereed) Published
Abstract [en]

Digital topology and geometry refers to the use of topologic and geometric properties and features for images defined in digital grids. Such methods have been widely used in many medical imaging applications, including image segmentation, visualization, manipulation, interpolation, registration, surface-tracking, object representation, correction, quantitative morphometry etc. Digital topology and geometry play important roles in medical imaging research by enriching the scope of target outcomes and by adding strong theoretical foundations with enhanced stability, fidelity, and efficiency. This paper presents a comprehensive yet compact survey on results, principles, and insights of methods related to digital topology and geometry with strong emphasis on understanding their roles in various medical imaging applications. Specifically, this paper reviews methods related to distance analysis and path propagation, connectivity, surface-tracking, image segmentation, boundary and centerline detection, topology preservation and local topological properties, skeletonization, and object representation, correction, and quantitative morphometry. A common thread among the topics reviewed in this paper is that their theory and algorithms use the principle of digital path connectivity, path propagation, and neighborhood analysis. 

Keywords
Connected operators, connectivity and tracking, digital topology and geometry, distance transform, local topology, minimal path, object characterization, simple point, skeletonization, watersheds
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-262374 (URN)10.1109/TMI.2015.2417112 (DOI)000361245700015 ()25879908 (PubMedID)
Available from: 2015-08-28 Created: 2015-09-14 Last updated: 2017-12-04Bibliographically approved
Curic, V., Lindblad, J., Sladoje, N., Sarve, H. & Borgefors, G. (2014). A new set distance and its application to shape registration. Pattern Analysis and Applications, 17(1), 141-152
Open this publication in new window or tab >>A new set distance and its application to shape registration
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2014 (English)In: Pattern Analysis and Applications, ISSN 1433-7541, E-ISSN 1433-755X, Vol. 17, no 1, p. 141-152Article in journal (Refereed) Published
National Category
Discrete Mathematics
Identifiers
urn:nbn:se:uu:diva-220413 (URN)10.1007/s10044-012-0290-x (DOI)000330839400011 ()
Available from: 2012-08-23 Created: 2014-03-13 Last updated: 2018-12-18Bibliographically approved
Wernersson, E. L. G., Borodulina, S., Kulachenko, A. & Borgefors, G. (2014). Characterisations of fibre networks in paper using micro computed tomography images. Nordic Pulp & Paper Research Journal, 29(3), 468-475
Open this publication in new window or tab >>Characterisations of fibre networks in paper using micro computed tomography images
2014 (English)In: Nordic Pulp & Paper Research Journal, ISSN 0283-2631, E-ISSN 2000-0669, Vol. 29, no 3, p. 468-475Article in journal (Refereed) Published
National Category
Paper, Pulp and Fiber Technology
Identifiers
urn:nbn:se:uu:diva-236353 (URN)10.3183/NPPRJ-2014-29-03-p468-475 (DOI)000342682700012 ()
Available from: 2014-11-18 Created: 2014-11-18 Last updated: 2017-12-05Bibliographically approved
Sarve, H., Friberg, B., Borgefors, G. & Johansson, C. B. (2013). Introducing a novel analysis technique for osseointegrated dental implants retrieved 29 years postsurgery. Clinical Implant Dentistry and Related Research, 15(4), 538-549
Open this publication in new window or tab >>Introducing a novel analysis technique for osseointegrated dental implants retrieved 29 years postsurgery
2013 (English)In: Clinical Implant Dentistry and Related Research, ISSN 1523-0899, E-ISSN 1708-8208, Vol. 15, no 4, p. 538-549Article in journal (Refereed) Published
Abstract [en]

Purpose: To investigate osseointegration of oral implants, which were retrieved from a patient after 29 years in situ, we use novel three-dimensional analysis methods and visualization techniques that supplement conventional two-dimensional analysis. Materials and Methods: The sample processing involved nondecalcification and embedment in resin. Conventional two-dimensional histomorphometrical methods were conducted. Additionally, the quantification was extended to three-dimensional by using synchrotron radiation micro-computed tomography (SRmCT) technique and two relevant visualization methods for the three-dimensional data were introduced. Results: The three-dimensional results involved three-dimensional quantification and visualization of two implant samples with methods beyond state-of-the-art. Traditional two-dimensional histomorphometrical results revealed a mean bone-implant contact (BIC) of about 50%. In most samples, bone area (BA) was lower inside the treads compared with out-folded mirror images, which were confirmed by the three-dimensional quantification. The BIC along four selected regions showed highest percentages in the bottom/valley region and lowest in the thread-peak region. Qualitative observations revealed ongoing bone remodeling areas in all samples. The apical hole demonstrated high osseointegration. Conclusion: The novel techniques including an animation and an out-folding of BIC and BA enabled a simultaneous visualization of the three-dimensional material obtained from SRmCT data. However, the two-dimensional histological sections were needed for qualitative and quantitative evaluation of osseointegration and, thus, both methods are considered equally important.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2013
National Category
Medical Image Processing Biomaterials Science
Identifiers
urn:nbn:se:uu:diva-164627 (URN)10.1111/j.1708-8208.2011.00413.x (DOI)000322580400008 ()
Available from: 2011-12-15 Created: 2011-12-21 Last updated: 2017-12-08Bibliographically approved
Selig, B., Luengo Hendriks, C. L., Bardage, S., Daniel, G. & Borgefors, G. (2012). Automatic measurement of compression wood cell attributes in fluorescence microscopy images. Journal of Microscopy, 246(3), 298-308
Open this publication in new window or tab >>Automatic measurement of compression wood cell attributes in fluorescence microscopy images
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2012 (English)In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 246, no 3, p. 298-308Article in journal (Refereed) Published
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:uu:diva-175180 (URN)10.1111/j.1365-2818.2012.03621.x (DOI)000303993700010 ()
Available from: 2012-05-14 Created: 2012-06-04 Last updated: 2018-01-12Bibliographically approved
Curic, V., Luengo Hendriks, C. L. & Borgefors, G. (2012). Salience adaptive structuring elements. IEEE Journal on Selected Topics in Signal Processing, 6(7), 809-819
Open this publication in new window or tab >>Salience adaptive structuring elements
2012 (English)In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 6, no 7, p. 809-819Article in journal (Refereed) Published
Abstract [en]

Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Morphological operators with salience adaptive structuring elements shift edges with high salience to a less extent than those with low salience. Salience adaptive structuring elements are less flexible than morphological amoebas and their shape is less affected by noise in the image. Consequently, morphological operators using salience adaptive structuring elements have better properties.

Keywords
Adaptive mathematical morphology, anisotropic filtering, morphological amoebas, salience distance transform
National Category
Other Mathematics
Identifiers
urn:nbn:se:uu:diva-181248 (URN)10.1109/JSTSP.2012.2207371 (DOI)000310138400007 ()
Available from: 2012-09-20 Created: 2012-09-20 Last updated: 2017-12-07Bibliographically approved
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