Texture Segmentation Benchmark

0545221 - ÚTIA 2023 RIV US eng J - Journal Article
Mikeš, Stanislav - Haindl, Michal
Texture Segmentation Benchmark.
IEEE Transactions on Pattern Analysis and Machine Intelligence. Roč. 44, č. 9 (2022), s. 5647-5663. ISSN 0162-8828. E-ISSN 1939-3539
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : Benchmark * Image segmentation * Texture segmentation * (Un)supervised segmentation * Segmentation criteria * Scale, rotation and illumination invariants
OECD category: Robotics and automatic control
Impact factor: 23.6, year: 2022
Method of publishing: Limited access
http://library.utia.cas.cz/separaty/2021/RO/haindl-0545221.pdf https://ieeexplore.ieee.org/document/9416785

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.
Permanent Link: http://hdl.handle.net/11104/0322145