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Multispectral point cloud superpoint segmentation

Science China(Technological Sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer Technologies Application Kunming 650500China School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint segmentation method that jointly utilizes spatial Geometric and Spectral Information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

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维普期刊数据库

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FLIC: Fast linear iterative clustering with active search

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Computational Visual Media 2018年第4期4卷 333-348页

作者： Jiaxing Zhao Ren Bo Qibin Hou Ming-Ming Cheng Paul Rosin Nankai University Tianjin 300350China. Cardiff University WalesUnited Kingdom.

In this paper, we reconsider the clustering problem for image over-segmentation from a new perspective. We propose a novel search algorithm called"active search" which explicitly considers neighbor continuity. Based on this search method, we design a back-and-forth traversal strategy and a joint assignment and update step to speed up the algorithm. Compared to earlier methods, such as simple linear iterative clustering(SLIC) and its variants, which use fixed search regions and perform the assignment and the update steps separately, our novel scheme reduces the number of iterations required for convergence,and also provides better boundaries in the oversegmentation results. Extensive evaluation using the Berkeley segmentation benchmark verifies that our method outperforms competing methods under various evaluation metrics. In particular, our method is fastest,achieving approximately 30 fps for a 481 × 321 image on a single CPU core. To facilitate further research, our code is made publicly available.

关键词： image over-segmentation SLIC neighbor continuity back-and-forth traversal

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维普期刊数据库

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Bridge Crack Image segmentation Based on Improved Watershed Algorithm

Bridge Crack Image Segmentation Based on Improved Watershed ...

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第30届中国控制与决策会议

作者： Liang Zhang Wenguang Luo Yani Xu School of Electrical and Information Engineering Guangxi University of Science and Technology

In order to solve the problem of over-segmentation of bridge fractures by the watershed algorithm, an improved watershed segmentation algorithm based on threshold marker is proposed. Firstly, the original gradient image is obtained from the gray image by using morphological operation, and the second-order Butterworth low-pass filtering is performed on the original gradient image to obtain the low-frequency component of the gradient image. And then apply the best threshold for the use of Otsu method to be applied to the morphological extended minimum transform technique, and the technique is used to extract the local minimum value which is highly correlated with the bridge crack feature information from the low frequency components of the gradient image;Finally, the original gradient image is used to compose the minimum gradient of the original gradient image to obtain the modified gradient image, and watershed segmentation is performed on these gradient images. The experimental results show that the crack image of the bridge is accurate and clear, and the over-segmentation phenomenon is effectively reduced.

关键词： Bridge Crack Watershed Algorithm Butterworth Low-pass Filter over-segmentation Local Minimum

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A New segmentation Method of CR Images Based on Discrete Wavelet Transform and Mathematics Morphology

A New Segmentation Method of CR Images Based on Discrete Wav...

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20th Congress of the International Commission for Optics

作者： LI Zhea,b and . HUANG Lian-qingaa Changchun Institute of Optics ,Fine Mechanics and Physics of Chinese Academy of Sciences,Changchun, China b Postgraduate School of Chinese Academy of Sciences, Beijing, China

In this paper, we propose a segmentation method of CR(computed radiography) images with being rid of under-segmentation and over-segmentation. An under-segmentation occurs when pixels belonging to dif

关键词： Watershed Algorithm Under-segmentation Discrete Wavelet Transform CR image over-segmentation

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