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In this paper, a multi-level image segmentation method using between-class variance (Otsu) based on improved bat algorithm (DWBA) with dynamically adjusting inertia weight and velocity stratification theory is proposed. DWBA algorithm has strong global search ability at the beginning. Then, the local search capability is enhanced with numbers increasing of iterations. More importantly, the performance of DWBA further improved, because bats with different fitness values have diverse velocities. Furthermore, an improved local search strategy is proposed to avoid the current best solution being replaced during iterations. The experimental results established that the proposed DWBA algorithm obtains better outcome than other algorithms.<\/jats:p>","DOI":"10.3233\/jifs-182806","type":"journal-article","created":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T15:02:47Z","timestamp":1562684567000},"page":"1399-1413","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["An improved bat algorithm and its application in multi-level image segmentation"],"prefix":"10.1177","volume":"37","author":[{"given":"Xiaofeng","family":"Yue","sequence":"first","affiliation":[{"name":"School of Mechatronic Engineering, Changchun University of Technology, Changchun, PR China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, Changchun University of Technology, Changchun, PR China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,7,9]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"GonzalezR.C. 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