Performance comparison and evaluation of vari-ous segmentation methods

  • Abstract
  • Keywords
  • References
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  • Abstract

    Image segmentation is the most important method in the concept of image processing. It helps in analyzing the image accurately in many applications. It is generally used to assign or name, a label to individual pixels in an image, so that labels with similar name share common features. These related pixels result in same color, texture, or intensity. It also helps in identifying lines, curves and objects. These kinds of results help in different applications in the field of medical imaging, 3D constructions, etc. There are different kinds of segmentation methods already available for such applications. This paper briefs and compares three different types of segmentation methods like multithreshold method, watershed method and normalized cut method. It is compared based on computational time, complexity and number of clusters of the different methods used in the image.

  • Keywords

    Multithreshold; Watershed; Normalised Cut.

  • References

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Article ID: 9687
DOI: 10.14419/ijet.v7i2.9687

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