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Texture Segmentation Benchmark
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SYSNO ASEP 0545221 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Texture Segmentation Benchmark Author(s) Mikeš, Stanislav (UTIA-B) RID
Haindl, Michal (UTIA-B) RID, ORCIDNumber of authors 2 Source Title IEEE Transactions on Pattern Analysis and Machine Intelligence. - : IEEE Computer Society - ISSN 0162-8828
Roč. 44, č. 9 (2022), s. 5647-5663Number of pages 16 s. Publication form Print - P Language eng - English Country US - United States Keywords Benchmark ; Image segmentation ; Texture segmentation ; (Un)supervised segmentation ; Segmentation criteria ; Scale, rotation and illumination invariants Subject RIV BD - Theory of Information OECD category Robotics and automatic control R&D Projects GA19-12340S GA ČR - Czech Science Foundation (CSF) Method of publishing Limited access Institutional support UTIA-B - RVO:67985556 UT WOS 000836666600081 EID SCOPUS 85105053349 DOI 10.1109/TPAMI.2021.3075916 Annotation The Prague texture segmentation data-generator and benchmark (\href{https://mosaic.utia.cas.cz}{mosaic.utia.cas.cz}) is a web-based service designed to mutually compare and rank (recently nearly 200) different static and dynamic texture and image segmenters, to find optimal parametrization of a segmenter and support the development of new segmentation and classification methods. The benchmark verifies segmenter performance characteristics on potentially unlimited monospectral, multispectral, satellite, and bidirectional texture function (BTF) data using an extensive set of over forty prevalent criteria. It also enables us to test for noise robustness and scale, rotation, or illumination invariance. It can be used in other applications, such as feature selection, image compression, query by pictorial example, etc. The benchmark's functionalities are demonstrated in evaluating several examples of leading previously published unsupervised and supervised image segmentation algorithms. However, they are used to illustrate the benchmark functionality and not review the recent image segmentation state-of-the-art. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2023 Electronic address https://ieeexplore.ieee.org/document/9416785
Number of the records: 1