• khalid Abduljabbar Department of Electrical Engineering, College of Engineering, Salahaddin University-Erbil, Kurdistan region, Iraq.
  • GORAN W. HAMAALI Department of Electrical Engineering, College of Engineering, Salahaddin University-Erbil, Kurdistan region, Iraq.
  • DIARY. R. SULAIMAN Department of Electrical Engineering, College of Engineering, Salahaddin University-Erbil, Kurdistan region, Iraq.




Image Segmentation, Thresholding, Optimization, OTSU Technique, PSO


The process of image segmentation is how to divide images into regions with similar properties. Threshold-based image segmentation is a multidimensional optimization problem that has been highlighted as one of the most significant image pre-processing approaches. This paper proposes an efficient technique for optimizing real time image segmentation. The approach of image thresholding may be regarded an optimization objective, and it will be discovered by using Otsu's technique in conjunction with Particle Swarm Optimization basics (PSO). For real-time validation, the suggested technique was tested on several images in real time using the PSO algorithm.  The simulation results showed that, when compared to Otsu's approach, the PSO algorithm gives the most efficient outcomes in real-time applications with an improved execution time.


A Mohsen, F. M., Hadhoud, M. M., Elkom, S., & Khalid Amin, E. (2011.). A new Optimization-Based Image Segmentation method By Particle Swarm Optimization. In IJACSA) International Journal of Advanced Computer Science and Applications.

Bhandari, A. K., Singh, V. K., Kumar, A., & Singh, G. K. (2014). Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy. Expert Systems with Applications

Chin-Wei, B., & Rajeswari, M. (2010). Multiobjective Optimization Approaches in Image Segmentation-The Directions and Challenges. In Int. J. Advance. Soft Comput. Appl (Vol. 2, Issue www.i-csrs.org

Ciesielski, K. C., & Udupa, J. K. (2007). A general theory of image segmentation: level set segmentation in the fuzzy connectedness framework. Medical Imaging 2007: Image Processing, 6512, 65120W. https://doi.org/10.1117/12.706271

Cohen, A. R. (2014). Extracting meaning from biological imaging data. Molecular Biology of the Cell, 25(22), 3470–3473. https://doi.org/10.1091/mbc.E14-04-0946

Goh, T. Y., Basah, S. N., Yazid, H., Aziz Safar, M. J., & Ahmad Saad, F. S. (2018). Performance analysis of image thresholding: Otsu technique. Measurement: Journal of the International Measurement Confederation, 114, 298–307. https://doi.org/10.1016/j.measurement.2017.09.052

Houssein, E. H., Helmy, B. E., Oliva, D., Elngar, A. A., & Shaban, H. (2021). A Novel Black Widow Optimization Algorithm for Multilevel Thresholding Image Segmentation. Expert Syst. Appl., 167(C). https://doi.org/10.1016/j.eswa.2020.114159

Lokhande, N. M., & Pujeri, R. v. (2018). Novel Image Segmentation Using Particle Swarm Optimization. Proceedings of the 2018 8th International Conference on Biomedical Engineering and Technology, 46–50. https://doi.org/10.1145/3208955.3208962

Naga, B., Divya, G., & Sowjanya, K. (April, 2015) Otsu’s Method of Image Segmentation using Particle Swarm Optimization Technique.


Otsu, N. (1979). A threshold selection method from gray level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9, 62–66.

Priyanka Vijay C Patil, P. N. (2016). Gray Scale Image Segmentation using OTSU Thresholding Optimal Approach J4R-Journal for Research Gray Scale Image Segmentation using OTSU Thresholding Optimal Approach. www.journalforresearch.org

Sarkar, S., Sen, N., Kundu, A., Das, S., & Sinha Chaudhuri, S. (2013). A differential evolutionary multilevel segmentation of near infra-red images using Renyi’s entropy. https://doi.org/10.1007/978-3-642-35314-7_79

Chapagain, Prerak, "Optimization Techniques for Image Processing" (2019). Senior Honors Theses. 133. https://scholarworks.uno.edu/honors_theses/133

Raju, Srujan. (2020). Review of Optimization Methods of Medical Image Segmentation. Advances in Intelligent Systems and Computing. 1090. 213-218. 10.1007/978-981-15-1480-7_17.

Bryan S. Morse. (2000). Lecture 4: Thresholding. The university OF Edinburgh, school of informatics. https://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/MORSE/threshold.pdf





Mathematics ,Physics and Engineering Researches