Abstract
The aim of this article is to present research involving the employment of intelligent methods for image analysis, particularly, the binarization process. In this case, the Flower Pollination Algorithm was used to optimize the internal parameters of the Niblack binarization algorithm. As a criterion for the quality of the proposed solution, the morphological parameter called the ‘bone volume’ (equivalent to porosity) is taken into account. The overarching objective of this study is to model the structure of cancellous bone based on the analysis of images derived from Micro-CT Scans.
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Kowalski, P.A. et al. (2019). Application of the Flower Pollination Algorithm in the Analysis of Micro-CT Scans. In: Cornejo, M., Kóczy, L., Medina, J., De Barros Ruano, A. (eds) Trends in Mathematics and Computational Intelligence. Studies in Computational Intelligence, vol 796. Springer, Cham. https://doi.org/10.1007/978-3-030-00485-9_1
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