Abstract
In this paper, a hybrid multi-cell image segmentation approach is proposed, based on the combination of active contour model (ACM) and ant colony optimization (ACO), for multi-cell image segmentation. This novel image segmentation algorithm integrates the characteristics of ACM model into the ACO with tractable and well defined energy and heuristic functions. Consequently, the problem of cell image segmentation is actually converted to search for the marks of cell contours by group of ants. Experiment results show that our proposed approach is more effective than several existing methods, and it is noted that our proposed approach is developed and implemented in LabVIEW as well with performance consistency.
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Acknowledgments
This work is supported by national natural science foundation of China (No.61273312), the natural science fundamental research program of higher education colleges in Jiangsu province (No. 14KJB510001) and the project of talent peak of six industries (DZXX-013).
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Jiang, D., Chen, Q., Xu, B., Lu, M. (2016). A Hybrid ACO-ACM Based Approach for Multi-cell Image Segmentation. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9712. Springer, Cham. https://doi.org/10.1007/978-3-319-41000-5_46
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DOI: https://doi.org/10.1007/978-3-319-41000-5_46
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