{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T15:32:03Z","timestamp":1760369523479,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,18]],"date-time":"2019-06-18T00:00:00Z","timestamp":1560816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scientific and Technological Research Program of Chongqing Municipal Education Commission","award":["KJ1704078"],"award-info":[{"award-number":["KJ1704078"]}]},{"name":"Research Funds of Chongqing Science and Technology Commission","award":["cstc2017jcyjAX0293"],"award-info":[{"award-number":["cstc2017jcyjAX0293"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a robust non-rigid feature matching approach for image registration with geometry constraints is proposed. The non-rigid feature matching approach is formulated as a maximum likelihood (ML) estimation problem. The feature points of one image are represented by Gaussian mixture model (GMM) centroids, and are fitted to the feature points of the other image by moving coherently to encode the global structure. To preserve the local geometry of these feature points, two local structure descriptors of the connectivity matrix and Laplacian coordinate are constructed. The expectation maximization (EM) algorithm is applied to solve this ML problem. Experimental results demonstrate that the proposed approach has better performance than current state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s19122729","type":"journal-article","created":{"date-parts":[[2019,6,19]],"date-time":"2019-06-19T02:42:46Z","timestamp":1560912166000},"page":"2729","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Robust Non-Rigid Feature Matching for Image Registration Using Geometry Preserving"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2215-9667","authenticated-orcid":false,"given":"Hao","family":"Zhu","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing, and Automotive Electronics and Embedded System Engineering Research Center, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}]},{"given":"Ke","family":"Zou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing, and Automotive Electronics and Embedded System Engineering Research Center, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}]},{"given":"Yongfu","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing, and Automotive Electronics and Embedded System Engineering Research Center, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}]},{"given":"Ming","family":"Cen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing, and Automotive Electronics and Embedded System Engineering Research Center, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5856-2223","authenticated-orcid":false,"given":"Lyudmila","family":"Mihaylova","sequence":"additional","affiliation":[{"name":"Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2698","DOI":"10.1109\/JSEN.2014.2315838","article-title":"Ensemble Registration of Multisensor Images by a Variational Bayesian Approach","volume":"14","author":"Zhu","year":"2014","journal-title":"IEEE Sens. 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