Skip to main content

Content-Based Color Image Retrieval Using Multi-Variate Feature Vectors

Buy Article:

$12.00 plus tax (Refund Policy)

This paper introduces a content-based image retrieval system which utilizes color, spatial frequency, and structural features of an object in the image. The major key color areas are extracted by image segmentation applying Bayesian classifier with k-means starter in CIELAB space and the color similarity is measured by summing up the inter-cluster color distances. The mutual correlations in DCT components are used to discriminate the spatial frequency features that carry textural details. In addition, a structural feature of image is simply characterized by down sampled color mosaic pattern. A target color image is retrieved by searching the image with the maximum similarity by cross correlations in the multi-dimensional feature vector space. Color similarity was indispensable to narrow the reliable candidate for almost all the tested images. Although an appropriate combination of spectral or structural features worked effective to retrieve the image with textural similarity, but we have not any definitive solution to select the frequency region yet. Finally, we report a method for evaluating the performance of our system based on psychophysical experiments using z-score.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: 2005-01-01

More about this publication?
  • For more than 30 years, IS&T's series of digital printing conferences have been the leading forum for discussion of advances and new directions in 2D and 3D printing technologies. A comprehensive, industry-wide conference that brings together industry and academia, this meeting includes all aspects of the hardware, materials, software, images, and applications associated with digital printing systems?particularly those involved with additive manufacturing and fabrication?including bio-printing, printed electronics, page-wide, drop-on-demand, desktop and continuous ink jet, toner-based systems, and production digital printing, as well as the engineering capability, optimization, and science involved in these fields. In 2016, the conference changed its name formally to Printing for Fabrication to better reflect the content of the meeting and the evolving technology of printing.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Membership Information
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more