Quantum inspired meta-heuristic approaches for automatic clustering of colour images

Title

Quantum inspired meta-heuristic approaches for automatic clustering of colour images

Creator

Dey A.; Dey S.; Bhattacharyya S.; Platos J.; Snasel V.

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, (Formula presented.) -test and Friedman test. Finally, the efficacy of the proposed algorithms has been proved with the help of quantitative evaluation of segmentation evaluation metrics. 2021 Wiley Periodicals LLC

Source

International Journal of Intelligent Systems, Vol-36, No. 9, pp. 4852-4901.

Date

2021-01-01

Publisher

John Wiley and Sons Ltd

Subject

automatic clustering; clustering validity measures; Friedman test; intelligent crow search optimization; quantum computing; segmentation evaluation metrics; Sobol's sensitivity analysis; t-test

Coverage

Dey A., Department of Computer Science and Engineering, RCC Institute of Information Technology, Kolkata, India; Dey S., Sukanta Mahavidyalaya, Dhupguri, India; Bhattacharyya S., Department of Computer Science and Engineering, Christ University, Bangalore, India; Platos J., Faculty of Electrical Engineering and Computer Science, VSB Technical University of Ostrava, Ostrava, Czech Republic; Snasel V., Faculty of Electrical Engineering and Computer Science, VSB Technical University of Ostrava, Ostrava, Czech Republic

Rights

All Open Access; Gold Open Access

Relation

ISSN: 8848173; CODEN: IJISE

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1002/int.22494

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107567991&doi=10.1002%2fint.22494&partnerID=40&md5=63827c3cf14ef450dfdc8464661af44b