Abstract
In this paper we present a ImageJ plugin for easy development of image segmentation (clustering) pipelines. Main focus of our approach is to provide scientists working with various images (especially biological and medical ones) with a tool making development of segmentation pipelines fast and easy. We accomplish this by introducing an extra abstraction layer to the ImageJ image segmentation approach – the feature space projection – that enables us to work with complex image descriptors and manage, visualize and test them directly from the plugin. Furthermore we give three separate ways of expressing such projections – one based on Java language, one based on external scripting and one on our custom simple Micro Matrix Language. The plugin can also serve as a fast method of rapid prototyping of image filters while its full ImageJ macro support makes it really easy to include it in ones current image processing methods.
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© 2014 Springer International Publishing Switzerland
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Czarnecki, W.M. (2014). InFeST – ImageJ Plugin for Rapid Development of Image Segmentation Pipelines. In: Gruca, D., Czachórski, T., Kozielski, S. (eds) Man-Machine Interactions 3. Advances in Intelligent Systems and Computing, vol 242. Springer, Cham. https://doi.org/10.1007/978-3-319-02309-0_30
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DOI: https://doi.org/10.1007/978-3-319-02309-0_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02308-3
Online ISBN: 978-3-319-02309-0
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