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αLBP – a novel member of the Local Binary Pattern family based on α-cutting
University of Novi Sad, Faculty of technical sciences.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia. (Centre for Image Analysis)ORCID iD: 0000-0001-7312-8222
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia. (Centre for Image Analysis)ORCID iD: 0000-0002-6041-6310
2015 (English)In: Proc. 9th International Symposium on Image and Signal Processing and Analysis, IEEE , 2015, p. 13-18Conference paper, Published paper (Refereed)
Abstract [en]

Local binary pattern (LBP) descriptors have been popular in texture classification in recent years. They were introduced as descriptors of local image texture and their histograms are shown to be well performing texture features. In this paper we introduce two new LBP descriptors, αLBP and its improved variant IαLBP. We evaluate their performance in classification by comparing them with some of the existing LBP descriptors - LBP, ILBP, shift LBP (SLBP) and with one ternary descriptor - LTP. The texture descriptors are evaluated on three datasets - KTH-TIPS2b, UIUC and Virus texture dataset. The novel descriptor outperforms the other descriptors on two datasets, KTH-TIPS2b and Virus, and is tied for first place with ILBP on the UIUC dataset.

Place, publisher, year, edition, pages
IEEE , 2015. p. 13-18
Keywords [en]
Histograms, Binary codes, Accuracy, Fuzzy sets, Image processing, Noise
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-267294DOI: 10.1109/ISPA.2015.7306025ISI: 000378419400003ISBN: 978-1-4673-8032-4 (print)OAI: oai:DiVA.org:uu-267294DiVA, id: diva2:872652
Conference
ISPA 2015, September 7–9, Zagreb, Croatia
Funder
VINNOVAAvailable from: 2015-09-09 Created: 2015-11-19 Last updated: 2018-12-02

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Lindblad, JoakimSladoje, Natasa

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