Quantum inspired meta-heuristic approaches for automatic clustering of colour images
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F21%3A10248801" target="_blank" >RIV/61989100:27240/21:10248801 - isvavai.cz</a>
Result on the web
<a href="https://onlinelibrary.wiley.com/doi/10.1002/int.22494" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/int.22494</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/int.22494" target="_blank" >10.1002/int.22494</a>
Alternative languages
Result language
angličtina
Original language name
Quantum inspired meta-heuristic approaches for automatic clustering of colour images
Original language description
In this article, quantum inspired incarnations of two swarm based meta-heuristic algorithms, namely, Crow Search Optimization Algorithm and Intelligent Crow Search Optimization Algorithm have been proposed for automatic clustering of colour images. The performance and effectiveness of the proposed algorithms have been judged by experimenting on 15 Berkeley images and five publicly available real life images of different sizes. The validity of the proposed algorithms has been justified with the help of four different cluster validity indices, namely, Pakhira Bandyopadhyay Maulik, I-index, Silhouette and CS-measure. Moreover, Sobol's sensitivity analysis has been performed to tune the parameters of the proposed algorithms. The experimental results prove the superiority of proposed algorithms with respect to optimal fitness, computational time, convergence rate, accuracy, robustness, t-test and Friedman test. Finally, the efficacy of the proposed algorithms has been proved with the help of quantitative evaluation of segmentation evaluation metrics.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Intelligent Systems
ISSN
0884-8173
e-ISSN
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Volume of the periodical
36
Issue of the periodical within the volume
9
Country of publishing house
US - UNITED STATES
Number of pages
50
Pages from-to
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UT code for WoS article
000658908200001
EID of the result in the Scopus database
2-s2.0-85107567991