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Networks and network-like structures are amongst the central building blocksof many technological and biological systems. Given a mathematical graphrepresentation of a network, methods from graph theory enable a preciseinvestigation of its properties. Software for the analysis of graphs is widelyavailable and has been applied to graphs describing large scale networks suchas social networks, protein-interaction networks, etc. In these applications,graph acquisition, i.e., the extraction of a mathematical graph from a network,is relatively simple. However, for many network-like structures, e.g. leafvenations, slime molds and mud cracks, data collection relies on images wheregraph extraction requires domain-specific solutions or even manual. Here weintroduce Network Extraction From Images, NEFI, a software tool thatautomatically extracts accurate graphs from images of a wide range of networksoriginating in various domains. While there is previous work on graphextraction from images, theoretical results are fully accessible only to anexpert audience and ready-to-use implementations for non-experts are rarelyavailable or insufficiently documented. NEFI provides a novel platform allowingpractitioners from many disciplines to easily extract graph representationsfrom images by supplying flexible tools from image processing, computer visionand graph theory bundled in a convenient package. Thus, NEFI constitutes ascalable alternative to tedious and error-prone manual graph extraction andspecial purpose tools. We anticipate NEFI to enable the collection of largerdatasets by reducing the time spent on graph extraction. The analysis of thesenew datasets may open up the possibility to gain new insights into thestructure and function of various types of networks. NEFI is open source andavailable http://nefi.mpi-inf.mpg.de.

NEFI: Network Extraction From Images