| Full text | |
| Author(s): |
Ribas, Lucas C.
;
Scabini, Leonardo F. S.
;
Sa Junior, Jarbas Joaci de Mesquita
;
Bruno, Odemir M.
Total Authors: 4
|
| Document type: | Journal article |
| Source: | PATTERN ANALYSIS AND APPLICATIONS; v. 27, n. 1, p. 12-pg., 2024-03-01. |
| Abstract | |
Texture is a visual attribute largely used in many problems of image analysis. Many methods that use learning techniques have been proposed for texture discrimination, achieving improved performance over previous handcrafted methods. In this paper, we present a new approach that combines a learning technique and the complex network (CN) theory for texture analysis. This method takes advantage of the representation capacity of CN to model a texture image as a directed network and then uses the topological information of vertices to train a randomized neural network. This neural network has a single hidden layer and uses a fast learning algorithm to learn local CN patterns for texture characterization. Thus, we use the weights of the trained neural network to compose a feature vector. These feature vectors are evaluated in a classification experiment in four widely used image databases. Experimental results show a high classification performance of the proposed method compared to other methods, indicating that our approach can be used in many image analysis problems. (AU) | |
| FAPESP's process: | 23/04583-2 - Pattern recognition in images based on artificial neural networks and complex systems: from handcrafted descriptor extraction to automated learning |
| Grantee: | Lucas Correia Ribas |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 19/07811-0 - Artificial neural networks and complex networks: an integrative study of topological properties and pattern recognition |
| Grantee: | Leonardo Felipe dos Santos Scabini |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 18/22214-6 - Towards a convergence of technologies: from sensing and biosensing to information visualization and machine learning for data analysis in clinical diagnosis |
| Grantee: | Osvaldo Novais de Oliveira Junior |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 21/09163-6 - Network science for optimizing artificial neural networks on computer vision |
| Grantee: | Leonardo Felipe dos Santos Scabini |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| FAPESP's process: | 18/22214-6 - Towards a convergence of technologies: from sensing and biosensing to information visualization and machine learning for data analysis in clinical diagnosis |
| Grantee: | Osvaldo Novais de Oliveira Junior |
| Support Opportunities: | Research Projects - Thematic Grants |