Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/5861,
  title    = {Salient Points Reduction for Content-Based Image Retrieval},
  author    = {Yao-Hong Tsai},
  country   = {Taiwan},
  institution={Hsuan Chuang University},
  abstract  = {Salient points are frequently used to represent local
properties of the image in content-based image retrieval. In this paper,
we present a reduction algorithm that extracts the local most salient
points such that they not only give a satisfying representation of an
image, but also make the image retrieval process efficiently. This
algorithm recursively reduces the continuous point set by their
corresponding saliency values under a top-down approach. The
resulting salient points are evaluated with an image retrieval system
using Hausdoff distance. In this experiment, it shows that our method
is robust and the extracted salient points provide better retrieval
performance comparing with other point detectors.},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {3},
  number    = {1},
  year      = {2009},
  pages     = {87 - 90},
  ee        = {http://waset.org/publications/5861},
  url       = {http://waset.org/Publications?p=25},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 25, 2009},
}