An image segmentation method using logarithmic kbest gravitational search algorithm based superpixel clustering

  • Himanshu MittalEmail author
  • Mukesh Saraswat
Special Issue


Image segmentation partitions an image into coherent and non-overlapping regions. Due to variations of visual patterns in images, it is a challenging problem. This paper introduces a new superpixel-based clustering method to efficiently perform the image segmentation. In the proposed method, initially superpixels from an image are obtained. The superpixels are further clustered into the required number of regions by a newly proposed variant of gravitational search algorithm namely; logarithmic kbest gravitational search algorithm. Experiments are conducted on the Berkeley Segmentation Dataset and Benchmark (BSDS500). It is affirmed from both visual and numerical analyses that the proposed method is efficacious and accurate in segmenting an image than the other considered segmentation methods.


Superpixel clustering Gravitational search algorithm Kmeans BSDS500 



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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Jaypee Institute of Information TechnologyNoidaIndia

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