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However, it faces three big challenges: (1) how to adaptively determine the number of multiple thresholds; (2) how to overcome the sensitivity to image noise; (3) how to perform multilevel thresholding under several segmentation requirements. In order to solve these problems, an adaptive multilevel thresholding algorithm based on multiobjective artificial bee colony optimization (AMT-MABCO) segmentation is presented for noisy image in this paper. To improve the robustness of AMT-MABCO to image noise, a line intercept histogram which considers both the intensity and coordinate information in the neighborhood of the pixels is firstly utilized to define a novel between-class variance function as one fitness function. Then, an interval-valued fuzzy entropy function is constructed as another fitness function to deal with the blurred characteristic in images. AMT-MABCO tries to obtain a compromising multilevel thresholding result under these two segmentation requirements. To adaptively determine the number of thresholds, a grouping population initialization and evaluation strategies are proposed in AMT-MABCO. Furthermore, two novel search equations are constructed in AMT-MABCO to generate candidate solutions in the employed bees and onlookers phases, respectively. Experimental results show that AMT-MABCO outperforms state-of-the-art thresholding methods in noise robustness and segmentation performance.<\/jats:p>","DOI":"10.3233\/jifs-191083","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T13:01:56Z","timestamp":1591707716000},"page":"305-323","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Adaptive multilevel thresholding based on multiobjective artificial bee colony optimization for noisy image segmentation"],"prefix":"10.1177","volume":"39","author":[{"given":"Feng","family":"Zhao","sequence":"first","affiliation":[{"name":"Key Laboratory of Electronic Information Application Technology for Scene Investigation, Ministry of Public Security, Xi\u2019an, P. R. China"},{"name":"School of Communications and Information Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, P. R. 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