Abstract
Image segmentation is the problem of finding the homogeneous regions (segments) in an image. The fuzzy connectedness has been applied in image segmentation, and segmented the object accurately. In recent years, how to find the reference seeds automatically for multiple objects image segmentation and speed up the process of large images segmentation as important issues to us. In this work we present a novel TABU search-based approach to choose the reference seeds adaptively and use a vertex set expanding method for fuzzy object extraction in image segmentation. This proposed algorithm would be more practical and with a lower computational complexity than others. The results obtained on real image confirm the validity of the proposed approach.
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Zhang, X., Zhang, Y., Wang, W., Li, Y. (2007). A Novel Approach for Fuzzy Connected Image Segmentation. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_11
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DOI: https://doi.org/10.1007/978-3-540-71441-5_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71440-8
Online ISBN: 978-3-540-71441-5
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