期刊
DIGITAL SIGNAL PROCESSING
卷 37, 期 -, 页码 53-64出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.dsp.2014.10.006
关键词
Membrane computing; Cell-like P systems; Image segmentation; Multi-level thresholding; Histogram
资金
- National Natural Science Foundation of China [61170030]
- Chunhui Project Foundation of the Education Department of China [Z2012025, Z2012031]
- Research Fund of Sichuan Key Technology Research and Development Program [2013GZX0155]
- Open Research Funds of Key Laboratory of High Performance Scientific Computing [SZE2012-002]
- Intelligent Network Information Processing, China [SZJJ2012-030]
The conventional methods are not effective and efficient for image multi-level thresholding due to timeconsuming and expensive computation cost. The multi-level thresholding problem can be posed as an optimization problem, optimizing some thresholding criterion. In this paper, membrane computing is introduced to propose an efficient and robust multi-level thresholding method, where a cell-like P system with the nested structure of three layers is designed as its computing framework. Moreover, an improved velocity-position model is developed to evolve the objects in membranes based on the special membrane structure and communication mechanism of objects. Under the control of evolution-communication mechanism of objects, the cell-like P system can efficiently exploit the best multi-level thresholds for an image. Simulation experiments on nine standard images compare the proposed multi-level thresholding method with several state-of-the-art multi-level thresholding methods and demonstrate its superiority. (C) 2014 Elsevier Inc. All rights reserved.
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