slugImproved Image Segmentation Using Dirichlet Process Multiple-View Learning With K-Means Clustering

Abstract

The image segmentation is a key challenge in image analysis. In this paper, a new method is proposed for performing interactive image segmentation extracting the object of interest from the non-trivial background, such as interactive multimedia applications. Although, fully automatic image segmentation algorithms have already been improved significantly, it is still not possible to apply an automatic image segmentation algorithm with a guaranteed performance in the general case. The image segmentation using multiple view learning is an efficient technique, but contains high error rate and also the smoothing factor is less but the segmentation ratio is less. Therefore, we proposed Image segmentation method using k-means algorithm along with Dirichlet process, which shows the improvement over these limitations. The proposed method improves the segmented part of the image as well as reduces the error rate of the image.

Authors and Affiliations

Poonam Mathan, Yogendra Kumar Jain

Keywords

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  • EP ID EP17735
  • DOI -
  • Views 362
  • Downloads 12

How To Cite

Poonam Mathan, Yogendra Kumar Jain (2014). slugImproved Image Segmentation Using Dirichlet Process Multiple-View Learning With K-Means Clustering. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(1), -. https://europub.co.uk/articles/-A-17735