• DocumentCode
    3045194
  • Title

    A Robust Two Signature Descriptor with Orientation Bins and Colour Codes for Enhanced Feature Matching

  • Author

    Imran, Saad Ali ; Aouf, Nabil

  • Author_Institution
    Dept. of Inf. & Syst. Eng., Cranfied Univ., Swindon, UK
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    3031
  • Lastpage
    3035
  • Abstract
    This paper proposes a novel feature descriptor combining signatures of intensity and colour for increased descriptive power. The proposed approach, instead of just the grey channel, uses all three channels of an RGB image, colour codes pixels around the feature corresponding to Gaussian clusters on a CIExy colour chart and then distributes them into bins combined with an intensity gradient histogram. It is shown for a number of examples - 12 image sets - that this descriptor, dubbed HISTInC, outperforms a standalone gradient histogram for a number of conditions, giving on average a 27% increase in precision. Furthermore, in the interest of preserving memory, HIST-InC with a reduced (by 22%) intensity signature is also tested and yields mixed results.
  • Keywords
    Gaussian processes; image colour analysis; image matching; CIExy colour chart; Gaussian clusters; HISTInC; RGB image; colour codes pixels; descriptive power; feature descriptor; feature matching; histogram-intensity and colour; intensity gradient histogram; intensity signatures; orientation bins; standalone gradient histogram; two signature descriptor; Computer vision; Conferences; Histograms; Image color analysis; Lighting; Mathematical model; Robustness; 2D features; colour images; feature matching; feature recognition; gradient histograms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.517
  • Filename
    6722270