Image Converting into Complex Networks : Scale- Level Segmentation Approach
Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Alexei Tikhomirov, Alessandra Rossodivita
Available Online December 2017.
- https://doi.org/10.2991/itsmssm-17.2017.88How to use a DOI?
- images , complex networks, conversion, topology, segmentation , spatial scales
- Image analysis and recognition is being a contemporary domain for successful tries to apply complex networks as an instrument for thorough studies. Researchers noted that an image having traditionally converted into a network (i.e. taking into account Euclidean distance between pixels only) possesses nodes with similar number of admissible links and the concomitant graph demonstrates a regular topology. As a rule, pixel intensity difference is considered to escape regularity and reach complex property of the network. Contrary revealing more specific traits of an image current study proposes scale segmentation views -local, medium and global - for an image to build a genuine complex network. Case study with two sample images manifests how the scales are connected with formation of a network topology.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Andrey Trufanov AU - Nikolay Kinash AU - Olga Berestneva AU - Alexei Tikhomirov AU - Alessandra Rossodivita PY - 2017/12 DA - 2017/12 TI - Image Converting into Complex Networks : Scale- Level Segmentation Approach BT - IV International research conference "Information technologies in Science, Management, Social sphere and Medicine" (ITSMSSM 2017) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/itsmssm-17.2017.88 DO - https://doi.org/10.2991/itsmssm-17.2017.88 ID - Trufanov2017/12 ER -