Comparitive Analysis of Image Segmentation Techniques

  • Rohit Sardana Pursuing
  • Published 2013

Abstract

Image segmentation is the process of partitioning an image into multiple segments, so as to change the representation of an image into something that is more meaningful and easier to analyze. Several general-purpose algorithms and techniques have been developed for image segmentation. In this paper, we present ostu method, watershed method and ColorBased Segmentation Using K-Means Clustering for image segmentation. Then evaluation of these method is done using four evaluation metrics: probabilistic Rand index, global consistency error, variation of information and peak signal to noise ratio. We intend to find out the best algorithm using evaluation metrices.

6 Figures and Tables

Cite this paper

@inproceedings{Pursuing2013ComparitiveAO, title={Comparitive Analysis of Image Segmentation Techniques}, author={Rohit Sardana Pursuing}, year={2013} }