COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS

  • SumitKaur Research Scholar, Gurukashi University, TalwandiSaboo, India
  • Dr. R.K Bansal Dean Research, Gurukashi University, TalwandiSaboo, India
Keywords: Image segmentation, Morphological Processing, Superpixel

Abstract

Superpixel segmentation showed to be a useful preprocessing step in many computer vision applications. Superpixel’s purpose is to reduce the redundancy in the image and increase efficiency from the point of view of the next processing task. This led to a variety of algorithms to compute superpixel segmentations, each with individual strengths and weaknesses. Many methods for the computation of superpixels were already presented. A drawback of most of these methods is their high computational complexity and hence high computational time consumption. K mean based SLIC method shows better performance as compare to other while evaluating on the bases of under segmentation error and boundary recall, etc parameters.

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Published
2018-03-31
How to Cite
Kaur, S., & Bansal, R. (2018). COMPARATIVE ANALYSIS OF SUPERPIXEL SEGMENTATION METHODS . International Journal of Engineering Technologies and Management Research, 5(3), 1-9. https://doi.org/10.29121/ijetmr.v5.i3.2018.172