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image segmentation algorithm based on neutrosophic fuzzy clustering with non-local information

IET image PROCESSING 2020年第3期14卷 576-584页

作者： Wen, Jinyu Xuan, Shibin Li, Yuqi Peng, Qihui Gao, Qing Guangxi Univ Nationalities Sch Informat Sci & Engn Daxue East Rd 188 Nanning Peoples R China Nanchang Hangkong Univ Sch Informat Engn Fenghe South Ave 696 Nanchang Jiangxi Peoples R China

To improve the boundary processing ability and anti-noise performance of image segmentation algorithm?a neutrosophic fuzzy clustering algorithm based on non-local information is proposed here. Initially, the proposed approach uses the data distribution of deterministic subset to determine the clustering centre of the fuzzy subset. Besides, the fuzzy non-local pixel correlation is introduced into the neutrosophic fuzzy mean clustering algorithm. The experimental results on synthetic images, medical images and natural images show that the proposed method is more robust and more accurate than the existing clustering segmentation methods.

关键词： image segmentation fuzzy set theory pattern clustering nonlocal information antinoise performance image segmentation algorithm data distribution deterministic subset clustering centre fuzzy subset nonlocal pixel correlation neutrosophic fuzzy mean clustering algorithm synthetic images medical images natural images

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image segmentation algorithm based on improved fuzzy clustering

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6-Sup期22卷 13911-13921页

作者： Lei, Xiangxiao Ouyang, Honglin Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Changsha Social Work Coll Changsha 410004 Hunan Peoples R China

Fuzzy clustering algorithm is the main method of image segmentation, but it can't be widely used in various fields. Therefore, an image segmentation algorithm based on improved fuzzy clustering was proposed in this paper. The fuzzy clustering theory and analysis method were described in detail, and the research of image segmentation algorithm was discussed in this paper. And then the method of sub graph decomposition and region merging was used to improve the clustering method of fuzzy C mean clustering image segmentation algorithm and the algorithm was verified by an example. The results showed that the algorithm was feasible. Compared with other existing algorithms, the algorithm had more advantages in running time and image segmentation accuracy.

关键词： Fuzzy clustering image segmentation algorithm Improvement

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image segmentation algorithm Based on Cloud Model the Application of fMRI

Image Segmentation Algorithm Based on Cloud Model the Applic...

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International Conference on Intelligent Computation Technology and Automation

作者： Shi Yunqiang Yu Xianchuan Beijing Normal Univ CIST Beijing 100875 Peoples R China

ISBN: (纸本)9780769533575

This paper introduces a new method-the cloud model theory for the fMRI image processing which aims at the uncertainty of the fMRI image data and the flaws of the current medical image segmentation algorithm. The method takes full account of the uncertainty of fMRI data, through the production cloud, the cloud synthesis as well as the category determination, can be effective to carry on the classification to the image data, then realization to image segmentation. The experimental result indicates that, this method may be in the accurate segmentation fMRI image target sector, and surpasses the traditional the image segmentation algorithm.

关键词： image segmentation algorithm image data fMRI CLOUDS Clouds image segmentation flaws

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NSST and vector-valued C-V model based image segmentation algorithm

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IET image PROCESSING 2020年第8期14卷 1614-1620页

作者： Wang, Xianghai Zhao, Xiaoyang Zhu, Yihuan Su, Xin Liaoning Normal Univ Sch Geog Sci Dalian 116029 Liaoning Peoples R China Liaoning Normal Univ Sch Comp & Informat Technol Dalian 116029 Liaoning Peoples R China Liaoning Normal Univ Sch Math Dalian 116029 Liaoning Peoples R China

image segmentation is a process of partitioning an image into non-overlapping regions. Existing unsupervised image segmentation methods include level set, automatic thresholding and region-based CV mode and so on. However, image segmentation as a key technology in the field of image processing has not been solved indeed, especially for images with complex texture. For this reason, the authors proposed a novel image segmentation algorithm based on NSST and the vector-valued Chan-Vese (C-V) model. First, they obtained a multi-scale representation by exploiting the non-subsampled shearlet transform (NSST) to extract multi-dimensional data in the image. Afterwards, they gave the vector-valued C-V model, and applied it to all subbands of NSST, which are treated as a vector-valued image. By comparing with other class methods, the experimental results show that the proposed method has better visual effects and lower error rates. But at the same time, it is a little time consuming. The proposed method is reasonable and effective, by taking full advantages of each subband's directional information during its diffusion process, compared with traditional C-V model.

关键词： transforms image segmentation image fusion nonoverlapping regions unsupervised image segmentation methods automatic thresholding image processing image segmentation algorithm NSST vector-valued image vector-valued Chan-Vese model vector-valued C-V model nonsubsampled shearlet transform visual effects diffusion process

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3D sculpture technology innovation based on image segmentation algorithm

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SOFT COMPUTING 2023年 1-10页

作者： Zhang, Xincheng Ge, Chunyu Jiamusi Univ Fine Arts Coll Jiamusi 154007 Peoples R China Jiamusi Univ Sch Mat Sci & Engn Jiamusi 154007 Peoples R China

At present, 3D modeling technology is simplified due to the improvement of image segmentation algorithm and feature point detection and other related technologies, so it is widely used in major museums. For example, science and technology museums can display emerging scientific and technological models by using 3D modeling, while museums and art galleries can display works of art and antiques by using 3D modeling. By using 3D modeling to display, tourists can effectively enhance the sense of substitution. 3D sculpture is a brand new product under this technical background, which can enhance the vividness of the exhibition of works in the Expo Park, thus bringing tourists a better tour experience. Based on this background, this study introduces the image segmentation algorithm to adjust and optimize 3d sculpture works, and introduces the main optimization process. Then, modeling, modification and model reconstruction are carried out through the collection and calculation of multi angle pictures. In this process, file content import, model data import and 3d object image import are required. The simulation results show that the optimized 3d model can effectively improve the frame rate performance of the model, but also reduce the volume, number of faces and vertex points of the model to a certain extent. It is an effective and innovative research work to optimize 3d sculpture by using image segmentation algorithm. This paper introduces the image segmentation algorithm into the field of 3d sculpture to achieve technological innovation.

关键词： image segmentation algorithm 3D sculpture Technology and process Innovation research

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Modified two-dimensional Otsu image segmentation algorithm and fast realisation

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IET image PROCESSING 2012年第4期6卷 426-433页

作者： Chen, Q. Zhao, L. Lu, J. Kuang, G. Wang, N. Jiang, Y. Natl Univ Def Technol Sch Elect Sci & Technol Changsha 410073 Hunan Peoples R China

Traditional two-dimensional (2D) Otsu method supposes that the sum of probabilities of diagonal quadrants in 2D histogram is approximately one. This studies experiments and theory prove that the sum of probabilities of off-diagonal quadrants in 2D histogram is not always very small and this could not be neglected. Therefore the assumption mentioned above in 2D Otsu method is inadequately reasonable. In this study, an improved 2D Otsu segmentation method and recursive algorithm are proposed. By calculating probabilities of diagonal quadrants in 2D histogram separately, modified method is acquired. Experimental results show that proposed method can obtain better performance of segmentation than the traditional 2D Otsu method. The computation complexity of improved 2D Otsu method is equal to traditional 2D Otsu method.

关键词： Recursive algorithms image segmentation algorithm Diagonal Quadrant histograms

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Real-time plant image segmentation algorithm under natural outdoor light conditions

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NEW ZEALAND JOURNAL OF AGRICULTURAL RESEARCH 2007年第5期50卷 847-854页

作者： Ji, Ronghua Fu, Zetian Qi, Lijun China Agr Univ Coll Engn Beijing Peoples R China China Agr Univ Coll Informat & Elect Engn Beijing Peoples R China

Variable rate pesticide application holds Great potential in precision agriculture where application efficiency depends mainly on plant recognition. The segmentation of the plant from the background is key to plant recognition. The work presented in this paper is a real-time segmentation algorithm that was developed to improve the quality of plant segmentation under natural outdoor light conditions. The plant images were greyed with the colour features H, a*, I3 and Cr respectively, and the plant was segmented from the grey images with a threshold that was computed by an iterative method. Experiments showed that segmentation was generally of good quality if the background was bare soil. The quality of segmentation declines if the images are greyed by H and Cr, and the quality remains stable if they are greyed by a* and I3 when the background is complicated, and, especially with heavy shadows. With respect to segmentation speed, that greyed by Cr was the fastest and that greyed by a* was slowest amongst the four.

关键词： image segmentation algorithm colour features threshold

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A Pyramidal image segmentation algorithm

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JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2010年第12期55卷 1550-1560页

作者： Chochia, P. A.

The problem of image segmentation (division into homogeneous regions) basing on color and texture region differences is considered. A two-level hierarchical pyramidal segmentation algorithm is proposed for solution of this problem. The homogeneity criterion is the estimated adjacency of the image elements and regions in the combined color-texture feature space. A metric in this space is introduced and studied. The results are verified on a set of test images of different types. DOI: 10.1134/S1064226910120296

关键词： image segmentation algorithm image segmentation Color instrument transmitters Eigenvector pixel PROBLEM SOLUTION

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Development of English translation online teaching system and service function improvement based on image segmentation algorithm

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SOFT COMPUTING 2023年第12期27卷 8415-8424页

作者： Qiao, Hongliang An, Lina Cao, Maojun Northeast Petr Univ Sch Foreign Languages Daqing 163318 Peoples R China Northeast Petr Univ Sch Comp & Informat Technol Daqing 163318 Peoples R China

With the continuous progress of Internet technology, so there is a higher demand for English translation. In this context, this paper realizes the design and improvement of the online English translation system by combining the image segmentation algorithm. After the experimental test of the algorithm of this system, if there is a lot of salt-and-pepper noise in the target image in the actual system application process, the method designed in this paper can reflect a better processing effect. Based on the analysis of performance parameters, this method can effectively process Gaussian noise images with high precision. After the completion of the system design, this paper tests the system. From the test and operation results, the software has reached the design objectives and completed the work tasks. The English translation online teaching system can form a safe, stable and high-bandwidth English translation teaching network and can realize the connection of the whole network. Users can share various software and hardware resources, completed the design of a translation platform that can realize rapid English communication, share experience and discuss, to effectively improve the learner's initiative. In this paper, an effective online teaching system is designed by introducing image segmentation algorithm into the field of English translation.

关键词： image segmentation algorithm English translation Online teaching System design

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HRCT image segmentation algorithm Based on Tolerance Granular Space Model

HRCT Image Segmentation Algorithm Based on Tolerance Granula...

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IEEE International Conference on Granular Computing

作者： Xu Xinying Cao Tianrui Yan Chengdong Xie Gang Wu Zhifeng Taiyuan Univ Technol Coll Informat Engn Taiyuan 030024 Peoples R China Shanxi Med Univ Taiyuan 030024 Peoples R China

ISBN: (纸本)9781424448319

In order to resolve quantitative analysis of lung tissue, according to the features of the medicine CT image's complicated texture, a image segmentation approach based on region growing method and granular computing is presented in this paper This segmentation algorithm is based on tolerance granular space model of granular computing. First, describes chest high-resolution CT images (HRCT) as granules and establishes the tolerance granular space model. Then, this algorithm can chooses an image sub-block as the seed block according to the intension of tolerance granule and carries on the region growing segmentation according to the tolerance relations automatically. Extensive experiments and evaluations were carried out and the results illustrate that this method can segment HRCT image accurately and precisely, and can obtain the lung tissue removing the tiny blood vessel and the trachea.

关键词： Models, Space Lung Tissue region growing Tolerances Tolerance Tolerance Tolerance physiologic tolerance Granular computing image segmentation algorithm grainstone image segmentation images Trachea

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