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
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;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
DOI :
10.1109/SMC.2013.517