Performance Evaluation of Image Retrieval System using Non-parametric Techniques
Tranos Zuva, Seleman M. Ngwira, Sunday O. Ojo, Keneilwe Zuva
Journal of Multimedia Processing and Technologies, Vol. 4, No. 1, 2013.
DOI: 
Link: http://www.dline.info/jmpt/fulltext/v4n1/3.pdf
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 & 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.