Performance comparison and evaluation of vari-ous segmentation methods

  • Authors

    • Vikashini Venkatesh Christ (Deemed to be University)
    • Praveen P U
    2018-05-03
    https://doi.org/10.14419/ijet.v7i2.9687
  • Multithreshold, Watershed, Normalised Cut.

  • 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.

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  • How to Cite

    Venkatesh, V., & P U, P. (2018). Performance comparison and evaluation of vari-ous segmentation methods. International Journal of Engineering & Technology, 7(2), 663-666. https://doi.org/10.14419/ijet.v7i2.9687

    Received date: 2018-02-24

    Accepted date: 2018-03-21

    Published date: 2018-05-03