Amrehn M, Glasbrenner J, Steidl S, Maier A (2016)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2016
Publisher: Springer
City/Town: Berlin Heidelberg
Pages Range: 68-73
Conference Proceedings Title: Bildverarbeitung für die Medizin 2016
Event location: Charité - Universitätsmedizin Berlin
ISBN: 978-3-662-49465-3
URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Amrehn16-CEO.pdf
DOI: 10.1007/978-3-662-49465-3
Open Access Link: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Amrehn16-CEO.pdf
Image segmentation is a key technique in image processing with the goal to extract important objects from the image. This evaluation study focuses on the segmentation quality of three different interactive segmentation techniques, namely Region Growing, Watershed and the cellular automaton based GrowCut algorithm.
Three different evaluation measures are computed to compare the segmentation quality of each algorithm: Rand Index, Mutual Information, and the Dice Coefficient. For the images in the publicly available ground truth data base utilized for the evaluation, the GrowCut method has a slight advantage over the other two.
The presented results provide insight into the performance and the characteristics with respect to the image quality of each tested algorithm.
APA:
Amrehn, M., Glasbrenner, J., Steidl, S., & Maier, A. (2016). Comparative Evaluation of Interactive Segmentation Approaches. In Bildverarbeitung für die Medizin 2016 (pp. 68-73). Charité - Universitätsmedizin Berlin, DE: Berlin Heidelberg: Springer.
MLA:
Amrehn, Mario, et al. "Comparative Evaluation of Interactive Segmentation Approaches." Proceedings of the Bildverarbeitung für die Medizin, Charité - Universitätsmedizin Berlin Berlin Heidelberg: Springer, 2016. 68-73.
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