Work

Visibility Graphs for Image Processing

Year: 2019

Type: article

Abstract: The family of image visibility graphs (IVG/IHVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such\an 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. 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.

Source: IEEE Transactions on Pattern Analysis and Machine Intelligence

DOI: 10.1109/tpami.2019.2891742

Authors: Jacopo Iacovacci, Lucas Lacasa

Institutions: The Francis Crick Institute, Imperial College London, Queen Mary University of London

Language: English

Topic: Image Retrieval and Classification Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Wellcome Trust, Engineering and Physical Sciences Research Council

Awards: G144484103, SIG-NET: Exploring the interface between SIGnal processing and NETwork science