Automatic AFM Images Distortion Correction Based on Adaptive Feature Recognition Algorithm

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	Automatic AFM Images Distortion Correction Based on Adaptive Feature Recognition Algorithm
	Yang, Chengpeng 2,3; Wang, Shoujin 3; Hao, Chunxue 2,3; Yang Y(杨洋)1,2; Shi JL(施佳林)1,2; Yu P(于鹏)1,2
	2020
会议日期	November 6-8, 2023
会议地点	Shanghai, China
关键词	AFM edge detection adaptive threshold least squares fitting horizontal distortion
页码	4981-4986
英文摘要	Atomic Force Microscope (AFM) images will appear tilt and bending of the image background due to the tilt angle between the sample surface and the probe, thermal noise of system, or external vibration of environment. Feature recognition is very crucial for removing unstable imaging background when using the least square fitting method to horizontally correct the AFM full image, which the topography structures higher or lower than the sample substrate will affect the fitting correction results. To realize universal automatic correction of AFM images, this paper proposes an adaptive feature recognition algorithm based on improved image edge detection method to automatically identify, frame and mark the features and then remove the detorsion background using Least Squares Fitting Correction. The experiment results show that this method can realize adaptive feature recognition and automatic fitting correction of the whole image, and improve the correction accuracy.
产权排序	1
会议录	Proceedings - 2020 Chinese Automation Congress, CAC 2020
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-7687-1
WOS记录号	WOS:000678697005017
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/28369]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Yang, Chengpeng
作者单位	1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 3.School of Information and Control Engineering, Shenyang Jianzhu University
推荐引用方式 GB/T 7714	Yang, Chengpeng,Wang, Shoujin,Hao, Chunxue,et al. Automatic AFM Images Distortion Correction Based on Adaptive Feature Recognition Algorithm[C]. 见:. Shanghai, China. November 6-8, 2023.