基于非负正交矩阵分解的多视图聚类图像分割算法

doi:10.16451/j.cnki.issn1003-6059.202306006

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Abstract Multi-view graph clustering shows some advantages in dealing with nonlinear structured data, but it exhibits drawbacks such as the need of post-processing and low time efficiency. To solve this problem, a non-negative orthogonal matrix factorization based multi-view clustering image segmentation algorithm(NOMF-MVC ) is proposed. Firstly, multi-view data of an image is extracted, and the manifold learning nonlinear dimensionality reduction method is employed to obtain the spectral embedding matrix of each view. Corresponding spectral block structure is constructed and it is fused into a consistency graph matrix via designed adaptive weights. Secondly, the non-negative embedding matrix is obtained by the non-negative orthogonal matrix factorization of the consistency graph matrix. Finally, the clustering of multi-view features is performed by the non-negative embedding matrix, and thereby image segmentation results are yielded. Comparative experiments on five datasets show certain improvements in segmentation accuracy and time efficiency achieved by NOMF-MVC.

Key words： Manifold Learning Spectral Structure Fusion Non-negative Orthogonal Matrix Factorization Image Segmentation Multi-view Clustering

Received: 16 March 2023

ZTFLH:

TP391.41

Fund:National Natural Science Foundation of China(No.51875152), Natural Science Foundation of Shanxi Province(No.

Corresponding Authors: ZHANG Rongguo, Ph.D., professor. His research interests include image processing, computer vision and pattern recognition.

About author:: About Author:CAO Junhui, master student. Her research interests include image processing and computer vision.HU Jing, Ph.D., professor. Her research interests include image processing and pattern recognition.ZHANG Rui, Ph.D., associate professor. His research interests include image proce-ssing and computer vision.LIU Xiaojun, Ph.D., professor. Her research interests include modern design theory and method, pattern recognition.

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Cite this article:

ZHANG Rongguo,CAO Junhui,HU Jing等. Non-negative Orthogonal Matrix Factorization Based Multi-view Clustering Image Segmentation Algorithm[J]. Pattern Recognition and Artificial Intelligence, 2023, 36(6): 556-571.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202306006 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2023/V36/I6/556

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