A new topological descriptor for contextual feature indexing
Nicolas Piché, Farida Chériet, François Guibault · 2016
A local feature descriptor for image analysis is a tool of interest for many applications. In this paper we propose an in context feature descriptor. An instance of this descriptor corresponding to a specific feature includes information from all other features in the image; it is a feature in context descriptor. This descriptor is thus unique for a feature in an ensemble of features. Many medical and industrial imaging applications are possible, one of them could be anomaly detection. Automatic anomaly detection could be implemented using this technique, thanks to the fact that this descriptor forms a metric space. Metric spaces are useful for indexing purposes and for statistical analysis.