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However, processing quality depends on the detection accuracy of fiducial marks. Precise segmentation of fiducial marks from images can significantly improve detection accuracy. Due to the complex background of PCB images, there are significant challenges in the segmentation and detection of fiducial mark images. In this paper, the mARU-Net is proposed for the image segmentation of fiducial marks with complex backgrounds to improve detection accuracy. Compared with some typical segmentation methods in customized datasets of fiducial marks, the mARU-Net demonstrates good segmentation accuracy. Experimental research shows that, compared with the original U-Net, the segmentation accuracy of the mARU-Net is improved by 3.015%, while the number of parameters and training times are not increased significantly. Furthermore, the centroid method is used to detect circles in segmentation results, and the deviation is kept within 30 microns, with higher detection efficiency. The detection accuracy of fiducial mark images meets the accuracy requirements of PCB production.<\/jats:p>","DOI":"10.3390\/s23239347","type":"journal-article","created":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T03:45:56Z","timestamp":1700711156000},"page":"9347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Image Segmentation of Fiducial Marks with Complex Backgrounds Based on the mARU-Net"],"prefix":"10.3390","volume":"23","author":[{"given":"Xuewei","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310058, China"},{"name":"Inner Mongolia Autonomous Region Special Service Intelligent Robot Key Laboratory, Inner Mongolia University of Technology, Hohhot 010051, China"}]},{"given":"Jichun","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310058, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3576-1817","authenticated-orcid":false,"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Yanwu","family":"Feng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310058, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3987-1810","authenticated-orcid":false,"given":"Shufeng","family":"Tang","sequence":"additional","affiliation":[{"name":"Inner Mongolia Autonomous Region Special Service Intelligent Robot Key Laboratory, Inner Mongolia University of Technology, Hohhot 010051, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22487","DOI":"10.1364\/OE.460780","article-title":"Method for improving the speed and pattern quality of a DMD maskless lithography system using a pulse exposure method","volume":"30","author":"Choi","year":"2022","journal-title":"Opt. 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