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Visibility graphs for image processing
- Publication Year :
- 2018
-
Abstract
- The family of image visibility graphs (IVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image classification. We demonstrate that the link architecture of the image visibility graphs encapsulates relevant information on the structure of the images and we explore their potential as image filters and compressors. We introduce several graph features, including the novel concept of Visibility Patches, and show through several examples that these features are highly informative, computationally efficient and universally applicable for general pattern recognition and image classification tasks.<br />16 pages, codes available upon request
- Subjects :
- FOS: Computer and information sciences
Computer science
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
FOS: Physical sciences
Machine Learning (stat.ML)
Image processing
02 engineering and technology
Artificial Intelligence
Statistics - Machine Learning
0202 electrical engineering, electronic engineering, information engineering
Time series
Contextual image classification
business.industry
Applied Mathematics
Probability and statistics
Pattern recognition
White noise
Graph
Computational Theory and Mathematics
Computer Science::Computer Vision and Pattern Recognition
Physics - Data Analysis, Statistics and Probability
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Artificial intelligence
business
Data Analysis, Statistics and Probability (physics.data-an)
Software
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....db71ef361c7c3aa1322f095e33ff2999