Skip to main content
padlock icon - secure page this page is secure

Color Invariant For Person Images Indexing

Buy Article:

$17.00 + tax (Refund Policy)

Many colored object recognition methods tend to fail when the incident illumination varies. In the context of image indexing, a method is presented, which does not depend on lighting conditions. A new approach for indexing images of persons moving in areas in where the acquisition is monitored by color cameras is developed to cope with the variations of the lighting conditions. We consider that illumination changes can be described using a simple linear transform. For comparing two images, we transform the target one according to the query one by means of an original color histogram specification based on color invariant evaluation. For the purpose of indexing, we evaluate invariant color signatures of the query image and the transformed target image, through the use of the color co-occurrence matrices. Results of tests on real images are very encouraging, with substantially better performance than those of other methods tested.
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: January 1, 2002

More about this publication?
  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    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 papers 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
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