Abstract
A wide family of Mathematical Morphology tools are based on the geodesical propagation of sets of pixels called markers through a reference image. Different algorithms have been proposed to implement such a process. Some of them use queues, either classical or hierarchical, and offer interesting performances on classical computers. In this paper we present various Morphological Operators sharing this behaviour and their implementation using queues (hierarchical queues for watershed, grayscale reconstruction, etc, simple queues for extrema computation, connectivity analysis, etc). The structure of these algorithms is then analysed and we propose two main schemes which map all the previous generic algorithms. From this remark a specific hardware architecture is proposed and evaluated on real examples using a VHDL description and a simulation.
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© 1996 Kluwer Academic Publishers
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Noguet, D., Merle, A., Lattard, D. (1996). A Data Dependent Architecture Based on Seeded Region Growing Strategy for Advanced Morphological Operators. In: Maragos, P., Schafer, R.W., Butt, M.A. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0469-2_27
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DOI: https://doi.org/10.1007/978-1-4613-0469-2_27
Publisher Name: Springer, Boston, MA
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