Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation  

作　　者：Laith Abualigah Mahmoud Habash Essam Said Hanandeh Ahmad MohdAziz Hussein Mohammad Al Shinwan Raed Abu Zitar Heming Jia 

机构地区：[1]Computer Science Department,Prince Hussein Bin Abdullah Faculty for Information Technology,Al Al-Bayt University,Mafraq,25113,Jordan [2]Hourani Center for Applied Scientific Research,Al-Ahliyya Amman University,Amman,19328,Jordan [3]Faculty of Information Technology,Middle East University,Amman,11831,Jordan [4]Applied Science Research Center,Applied Science Private University,Amman,11931,Jordan [5]School of Computer Sciences,Universiti Sains Malaysia,11800,Pulau Pinang,Malaysia [6]Amman Arab University,Amman,Jordan [7]Department of Computer Information System,Zarqa University,P.O.Box 13132,Zarqa,Jordan [8]Deanship of E-Learning and Distance Education,Umm Al-Qura University,Makkah,21955,Saudi Arabia [9]Faculty of Information Technology,Applied Science Private University,Amman,11931,Jordan [10]Sorbonne Center of Artificial Intelligence,Sorbonne University-Abu Dhabi,Abu Dhabi,United Arab Emirates [11]School of Information Engineering,Sanming University,Sanming,365004,China

出　　处：《Journal of Bionic Engineering》2023年第4期1766-1790,共25页仿生工程学报（英文版）

摘　　要：This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding,called RSA-SSA.The proposed method introduces a better search space to find the optimal solution at each iteration.However,we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level thresholds.The obtained solutions by the proposed method are represented using the image histogram.The proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each level.The performance measure for the proposed method is valid by detecting fitness function,structural similarity index,peak signal-to-noise ratio,and Friedman ranking test.Several benchmark images of COVID-19 validate the performance of the proposed RSA-SSA.The results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.

关 键 词：BIOINSPIRED Reptile Search Algorithm Salp Swarm Algorithm Multi-level thresholding Image segmentation Meta-heuristic algorithm 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]