基于非负正交矩阵分解的多视图聚类图像分割算法

作者：Zhang Rongguo^*; Cao Junhui; Hu Jing; Zhang Rui; Liu Xiaojun

来源：Pattem Recognition and Aitificial Intelligence, 2023, 36(6): 556-571.

DOI：10.16451/j.cnki.issn1003-6059.202306006

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

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. ? 2023 Journal of Pattern Recognition and Artificial Intelligence.

• 单位
  合肥工业大学