Enhanced independent component analysis and fuzzy C-mean clustering based on novel bat algorithm for noisy image segmentation
Nabil Chetih,
Tawfik Thelaidjia,
Fatma Zohra Boudani
Abstract:Fuzzy c-means clustering is widely recognized as one of the most effective methods for image segmentation and achieving accurate classification. However, this method has two significant drawbacks: its sensitivity to noise and its convergence to local minimum clusters’ centroids. In this paper, we proposed a novel model called EIFCMNB, which incorporates enhanced independent component analysis (EICA), fuzzy c-means clustering (FCMC) and novel bat algorithm (NBA) for noise image segmentation. The suggested model… Show more
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