{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:41:17Z","timestamp":1760240477572,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T00:00:00Z","timestamp":1562025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51705299"],"award-info":[{"award-number":["51705299"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanxi Science and Technology Department Projects","award":["201801D221047"],"award-info":[{"award-number":["201801D221047"]}]},{"name":"Shanxi Transportation Holdings Group Science and Technology Projects Fund","award":["18-JKKJ-02"],"award-info":[{"award-number":["18-JKKJ-02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Image segmentation is a crucial topic in image analysis and understanding, and the foundation of target detection and recognition. Image segmentation, essentially, can be considered as classifying the image according to the consistency of the region and the inconsistency between regions, it is widely used in medical and criminal investigation, cultural relic identification, monitoring and so forth. There are two outstanding common problems in the existing segmentation algorithm, one is the lack of accuracy, and the other is that it is not widely applicable. The main contribution of this paper is to present a novel segmentation method based on the information entropy theory and multi-scale transform contour constraint. Firstly, the target contour is initially obtained by means of a multi-scale sample top-hat and bottom-hat transform and an improved watershed method. Subsequently, in terms of this initial contour, the interesting areas can be finely segmented out with an innovative 3D flow entropy method. Finally, the sufficient synthetic and real experiments proved that the proposed algorithm can greatly improve the segmentation effect. In addition, it is widely applicable.<\/jats:p>","DOI":"10.3390\/sym11070857","type":"journal-article","created":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T12:11:17Z","timestamp":1562069477000},"page":"857","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["3D Flow Entropy Contour Fitting Segmentation Algorithm Based on Multi-Scale Transform Contour Constraint"],"prefix":"10.3390","volume":"11","author":[{"given":"Hongtao","family":"Wu","sequence":"first","affiliation":[{"name":"Shanxi Transportation Technology Research &amp; Development Co., Ltd., Taiyuan 030032, China"}]},{"given":"Liyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Shanxi Transportation Technology Research &amp; Development Co., Ltd., Taiyuan 030032, China"}]},{"given":"Jinhui","family":"Lan","sequence":"additional","affiliation":[{"name":"School of Automation, University of Science and Technology Beijing, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3129","DOI":"10.12785\/amis\/080654","article-title":"Maximum entropy for image segmentation based on an adaptive particle swarm optimization","volume":"8","author":"Qi","year":"2014","journal-title":"Appl. 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