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<record>
  <title>Performance Evaluation of Image Retrieval System using Non-parametric Techniques</title>
  <journal>Journal of Multimedia Processing and Technologies</journal>
  <author>Tranos Zuva, Seleman M. Ngwira, Sunday O. Ojo, Keneilwe Zuva</author>
  <volume>4</volume>
  <issue>1</issue>
  <year>2013</year>
  <doi></doi>
  <url>http://www.dline.info/jmpt/fulltext/v4n1/3.pdf</url>
  <abstract>This paper considered performance of content based image retrieval system using image representation nonparametric algorithms. Performance comparison of Epanechnikov, Gaussian and Histogram non-parametric algorithms was done in a generic image retrieval system. Chan &amp; Vese and Cosine Angle Distance algorithms were used for segmentation and similarity matching respectively. The performance of the non-parametric techniques was measured using recall-precision curve and the Bullâ€™s Eye performance score. The experimental results showed that estimating techniques performed better than the absolute value technique. The study then looked at the limitations of these techniques.</abstract>
</record>
