A Novel Approach for Object Extraction Based On Linear Discriminant Analysis

Authors

  • G. Sukanya  M.Tech Student, Department of ECE, Svuce, Tirupati, Andhra Pradesh, India
  • S. Swarnalatha  Associate Professor, Department of ECE, Svuce, Tirupati, Andhra Pradesh, India

Keywords:

Object Extraction, PCA, LDA, k-means segmentation

Abstract

Multi view object Extraction plays a major role in tracking and many other applications. Recently different methods are used to extract the object along with boundaries in multi directions. Principal component analysis method is used to extract the object. This method fails due to the high dimensionality and high complexity. So, to overcome the above drawbacks proposed a method called linear discriminant analysis. In this method first extracting the features of the image and converting into the H,S and V planes. k-means segmentation performed to segment the foreground object and extract the boundaries of the object. Experimental results prove to be better and yields better performance when compared to the other state of art methods.

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Published

2018-04-30

Issue

Section

Research Articles

How to Cite

[1]
G. Sukanya, S. Swarnalatha, " A Novel Approach for Object Extraction Based On Linear Discriminant Analysis, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.522-530, March-April-2018.