Optimal multi-level thresholding with membrane computing

Description

The conventional methods are not effective and efficient for image multi-level thresholding due to time-consuming and expensive computation cost. The multi-level thresholding problem can be posed as anoptimization problem, optimizing some thresholding criterion. In this paper, membrane computing isintroduced to propose an efficient and robust multi-level thresholding method, where a cell-like P systemwith the nested structure of three layers is designed as its computing framework. Moreover, an improvedvelocity-position model is developed to evolve the objects in membranes based on the special membranestructure and communication mechanism of objects. Under the control of evolution-communicationmechanism of objects, the cell-like P system can efficiently exploit the best multi-level thresholds for animage. Simulation experiments on nine standard images compare the proposed multi-level thresholdingmethod with several state-of-the-art multi-level thresholding methods and demonstrate its superiority.

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National Natural Science Foundation of China No. 61170030

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Chunhui Project Foundation of the Education Department of China No. Z2012025

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Chunhui Project Foundation of the Education Department of China No. Z2012031

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Research Fund of Sichuan Key Technology Research and Development Program No. 2013GZX0155

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Open Research Funds of Key Laboratory of High Performance Scientific Computing No. SZJJ2012-002

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