[1]T. Y. Goh, S. N. Basah, H. Yazid, M. J. Aziz Safar, and F. S. Ahmad Saad, "Performance analysis of image thresholding: Otsu technique," Meas. J. Int. Meas. Confed., vol. 114, pp. 298–307, Jan. 2018, doi: 10.1016/j.measurement.2017.09.052.
[2] S. Pare, A. Kumar, G. K. Singh, and V. Bajaj, "Image Segmentation Using Multilevel Thresholding: A Research Review," Iranian Journal of Science and Technology - Transactions of Electrical Engineering, vol. 44, no. 1. Springer, Mar. 01, 2020, doi: 10.1007/s40998-019-00251-1.
[3] W. Liu et al., “Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm,” Appl. Sci., vol. 10, no. 9, 2020, doi: 10.3390/app10093225.
[4] J. Rahaman and M. Sing, “An efficient multilevel thresholding based satellite image segmentation approach using a new adaptive cuckoo search algorithm,” Expert Syst. Appl., vol. 174, no. January, p. 114633, 2021, doi: 10.1016/j.eswa.2021.114633.
[5] A. K. Bhandari, A. Kumar, S. Chaudhary, and G. K. Singh, “A novel color image multilevel thresholding based segmentation using nature inspired optimization algorithms,” Expert Syst. Appl., vol. 63, pp. 112–133, 2016, doi: 10.1016/j.eswa.2016.06.044.
[6] A. K. Bhandari, A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation, vol. 32, no. 9. Springer London, 2020.
[7] L. He and S. Huang, "An efficient krill herd algorithm for color image multilevel thresholding segmentation problem," Appl. Soft Comput. J., vol. 89, p. 106063, 2020, doi: 10.1016/j.asoc.2020.106063.
[8] A. K. Bhandari, A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation, vol. 32, no. 9. Springer London, 2020.
[9] Z. Yan, J. Zhang, Z. Yang, and J. Tang, "Kapur’s Entropy for Underwater Multilevel Thresholding Image Segmentation Based on Whale Optimization Algorithm,” IEEE Access, vol. 9, pp. 41294–41319, 2021, doi: 10.1109/ACCESS.2020.3005452.
[10] S. Wang, K. Sun, W. Zhang, and H. Jia, “Multilevel thresholding using a modified ant lion optimizer with opposition-based learning for color image segmentation,” Math. Biosci. Eng., vol. 18, no. 4, pp. 3092–3143, 2021, doi: 10.3934/mbe.2021155.
[11] S. Singh, N. Mittal, and H. Singh, A multilevel thresholding algorithm using HDAFA for image segmentation, vol. 25, no. 16. 2021.
[12] D. Wu and C. Yuan, “Threshold image segmentation based on improved sparrow search algorithm,” Multimed. Tools Appl., 2022, doi: 10.1007/s11042-022-13073-x.
[13] M. Abdel-Basset, V. Chang, and R. Mohamed, “A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems,” Neural Comput. Appl., vol. 33, no. 17, pp. 10685–10718, 2021, doi: 10.1007/s00521-020-04820-y.
[14] S. Pare, A. Kumar, V. Bajaj, and G. K. Singh, “An efficient method for multilevel color image thresholding using cuckoo search algorithm based on minimum cross entropy,” Appl. Soft Comput. J., vol. 61, pp. 570–592, Dec. 2017, doi: 10.1016/j.asoc.2017.08.039.
[15] M. Abdel-Basset, V. Chang, and R. Mohamed, “A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems,” Neural Comput. Appl., vol. 33, no. 17, pp. 10685–10718, 2021, doi: 10.1007/s00521-020-04820-y.
[16] J. Rahaman and M. Sing, “An efficient multilevel thresholding based satellite image segmentation approach using a new adaptive cuckoo search algorithm,” Expert Syst. Appl., vol. 174, no. January, p. 114633, 2021, doi: 10.1016/j.eswa.2021.114633.
[17] A. Sharma, R. Chaturvedi, S. Kumar, and U. K. Dwivedi, “Multilevel image thresholding based on Kapur and Tsallis entropy using firefly algorithm,” J. Interdiscip. Math., vol. 23, no. 2, pp. 563–571, Feb. 2020, doi: 10.1080/09720502.2020.1731976.
[18] A. K. Bhandari, A. Kumar, S. Chaudhary, and G. K. Singh, “A novel color image multilevel thresholding based segmentation using nature inspired optimization algorithms,” Expert Syst. Appl., vol. 63, pp. 112–133, Nov. 2016, doi: 10.1016/j.eswa.2016.06.044.
[19] X. Bao, H. Jia, and C. Lang, “A Novel Hybrid Harris Hawks Optimization for Color Image Multilevel Thresholding Segmentation,” IEEE Access, vol. 7, pp. 76529–76546, 2019, doi: 10.1109/ACCESS.2019.2921545.
[20] V. Rajinikanth, N. Dey, S. C. Satapathy, and A. S. Ashour, “An approach to examine Magnetic Resonance Angiography based on Tsallis entropy and deformable snake model,” Futur. Gener. Comput. Syst., vol. 85, pp. 160–172, 2018, doi: 10.1016/j.future.2018.03.025.