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Threshold image target segmentation technology based on intelligent algorithms

Y.X. Cai 1, Y.Y. Xu 1, T.R. Zhang 1, D.D. Li 1

1 Hengshui University, Hengshui, Hebei 053000, China

 PDF, 1044 kB

DOI: 10.18287/2412-6179-CO-630

Pages: 137-141.

Full text of article: English language.

Abstract:
This paper briefly introduces the optimal threshold calculation model and particle swarm optimization (PSO) algorithm for image segmentation and improves the PSO algorithm. Then the standard PSO algorithm and improved PSO algorithm were used in MATLAB software to make simulation analysis on image segmentation. The results show that the improved PSO algorithm converges faster and has higher fitness value; after the calculation of the two algorithms, it is found that the improved PSO algorithm is better in the subjective perspective, and the image obtained by the improved PSO segmentation has higher regional consistency and takes shorter time in the perspective of quantitative objective data. In conclusion, the improved PSO algorithm is effective in image segmentation.

Keywords:
particle swarm optimization, thresholding, image segmentation, relative basis.

Citation:
Cai YX, Xu YY, Zhang TR, Li DD. Threshold image target segmentation technology based on intelligent algorithms. Computer Optics 2020; 44(1): 137-141. DOI: 10.18287/2412-6179-CO-630.

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