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

Neighborhood and Haralick feature extraction for color texture analysis

Buy Article:

$17.00 + tax (Refund Policy)

In this paper, we propose to study the influence of the neighborhood used to process the color co-occurrence matrices on the quality of texture analysis.

First, we measure the discriminating power of Haralick features extracted from the color co-occurrence matrices of color images coded in 28 different color spaces, and we select the most discriminating one for different 3x3 neighborhoods. Then, we experimentally verify that the most discriminating feature space, built by using an iterative selection procedure, depends on the chosen neighborhood and finally we study the impact of the neighborhood choice on the classification results by using the same feature space but different neighborhoods.

Experimental results achieved with the Barktek database have firstly shown the adequacy between the discriminating power of the selected feature space and the rate of well-classified images. We have also seen that the choice of the neighborhood does not highly influence the selection of the most discriminating feature but has a significant impact on the quality of discrimination between the considered textures. Indeed, we have worked with textures which contain vertical patterns and have shown that the best classification results have been obtained with horizontal neighborhoods. The choice of the neighborhood depends consequently on the analysed textures.
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, 2008

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