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Graph-Based Image Matching for Indoor Localization
2019
Machine Learning and Knowledge Extraction
Graphs are a very useful framework for representing information. In general, these data structures are used in different application domains where data of interest are described in terms of local and spatial relations. In this context, the aim is to propose an alternative graph-based image representation. An image is encoded by a Region Adjacency Graph (RAG), based on Multicolored Neighborhood (MCN) clustering. This representation is integrated into a Content-Based Image Retrieval (CBIR)
doi:10.3390/make1030046
fatcat:kqreo5crjvagljzgzf2jv4lmhe