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High Curvature Stripe profile extraction Algorithm of Line Structured Light Measuring System

Journal of Shanghai Jiaotong university(Science) 2023年第5期28卷 560-568页

作者：孙昊杜宣吕娜崔斌赵辉 Department of Instrument Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

In the line structured light measuring system, the accuracy of the process of laser stripe directly affects the measurement results. Therefore, the extraction algorithm for the laser stripe, especially the surface with high reflection and high curvature, is very important. The imaging principle of line structured light, the light intensity distribution law of laser stripe and the extraction algorithm have been studied, and a stripe profile extraction method based on real light intensity distribution has been proposed. In this algorithm, fast region of interest extraction, stripe width estimation, and adaptive filtering on the striped image are performed. Then the energy center of the stripe at the sub-pixel level is extracted. Finally, the low-quality center points are eliminated, and the context information is used to recover the missing central points. Simulated images generated based on the imaging principle of line structured light and real experimental images were used to evaluate the accuracy and repeatability of the proposed method. The results show that the method behaves excellently at the edges of high-curvature stripes;the maximum error is only 1.6 pixels, which is 1/10 of the classic Steger algorithm;the experiment repeatability is only 8.8 μm, which is 2.7 times that of the Steger method. Therefore, the proposed method improves the accuracy of object contour extraction, and it is especially suitable for contour detection of objects with high curvature.

关键词： profile measurement line structured light profile extraction sub-pixel high curvature

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AMiner:Search and Mining of Academic Social Networks

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Data Intelligence 2019年第1期1卷 58-76页

作者： Huaiyu Wan Yutao Zhang Jing Zhang Jie Tang School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Information School Renmin University of ChinaBeijing 100872China

AMiner is a novel online academic search and mining system,and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors,papers,conferences,journals and *** system is subsequently able to extract researchers’profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name *** a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise *** addition,AMiner offers a set of researcher-centered functions,including social influence analysis,relationship mining,collaboration recommendation,similarity analysis and community *** system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.

关键词： Academic social networks profile extraction Name disambiguation Topic modeling Expertise Search Network mining

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