Boosted Aquila Arithmetic Optimization Algorithm for multi-level thresholding image segmentation

被引：1

作者：

Abualigah, Laith ^{[1
,6
,7
,8
,9
,10
,11
,12
]}

Al-Okbi, Nada Khalil ^{[2
,13
]}

Awwad, Emad Mahrous ^{[3
]}

Sharaf, Mohamed ^{[4
]}

Daoud, Mohammad Sh. ^{[5
]}

机构：

[1] Al Al Bayt Univ, Dept Comp Sci, Mafraq 25113, Jordan

[2] Univ Baghdad, Coll Sci Women, Dept Comp Sci, Baghdad, Iraq

[3] King Saud Univ, Coll Engn, Dept Elect Engn, POB 800, Riyadh 11421, Saudi Arabia

[4] King Saud Univ, Coll Engn, Dept Ind Engn, POB 800, Riyadh 11421, Saudi Arabia

[5] Al Ain Univ, Coll Engn, Abu Dhabi 112612, U Arab Emirates

[6] Al Ahliyya Amman Univ, Hourani Ctr Appl Sci Res, Amman 19328, Jordan

[7] Middle East Univ, MEU Res Unit, Amman 11831, Jordan

[8] Lebanese Amer Univ, Dept Elect & Comp Engn, Byblos 135053, Lebanon

[9] Sunway Univ, Sch Engn & Technol, Petaling Jaya 27500, Malaysia

[10] Appl Sci Private Univ, Appl Sci Res Ctr, Amman 11931, Jordan

[11] Isra Univ, Fac Informat Technol, Amman 11622, Jordan

[12] Yuan Ze Univ, Coll Engn, Taoyuan, Taiwan

[13] Putian Univ, New Engn Ind Coll, Putian 351100, Peoples R China

来源：

EVOLVING SYSTEMS | 2024年 / 15卷 / 04期

关键词：

Aquila optimizer (AO); Arithmetic optimization algorithm (AOA); Image segmentation; Multi-level threshold; X-ray COVID-19 images;

D O I：

10.1007/s12530-024-09576-7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The traditional threshold methods used for image segmentation are effective for bi-level thresholds. In the case of complex images that contain many objects or color images, the computational complexity is significantly elevated. Multi-level threshold methods for the segmentation of color images can be seen as a complicated optimization problem. In this paper, an improved version of the Arithmetic Optimization Algorithm, called AOAa, is proposed based on the efficient search operators of Aquila Optimizer to obtain optimal threshold values in various levels of color and gray images. Otsu and Kapur’s entropy methods are used in this study as objective functions. Experiments were conducted on 16 benchmark images; COVID-19, color, and gray. The results are analyzed regarding the fitness function, peak signal-to-noise ratio (PSNR), and structural index similarity (SSIM). The obtained results showed that the proposed method got better results than several other well-established methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. corrected publication 2024.

引用

页码：1427 / 1427

页数：1