Colour object recognition is heavily influenced by the variation in the scene illumination conditions. This paper proposes a set of illumination-invariant descriptors of image content. The descriptors are based on a moment-based approach to histogram comparison and, in the case of an object imaged under two different lighting conditions, permit a straightforward recovery of the illumination change involved. The efficacy of the descriptors is compared experimentally with a variety of existing techniques, using an established methodology and an existing purpose-built dataset. The evidence suggests that the new descriptors outperform existing techniques in the area of colour object recognition.
|Translated title of the contribution||Improved illumination-invariant descriptors for robust colour object recognition|
|Title of host publication||2002 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '02)|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||IV-3393 - IV-3396|
|Number of pages||4|
|Publication status||Published - May 2002|
|Event||2002 IEEE International Conference on Acoustics, Speech, and Signal Processing - Orlando, Florida, United States|
Duration: 13 May 2002 → 17 May 2002
|Conference||2002 IEEE International Conference on Acoustics, Speech, and Signal Processing|
|Abbreviated title||ICASSP '02|
|Period||13/05/02 → 17/05/02|
Bibliographical noteRose publication type: Conference contribution
Sponsorship: This work was sponsored by EPSRC grant GR/M84183 under the Link project Autoarch.
This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to email@example.com.
By choosing to view this document, you agree to all provisions of the copyright laws protecting it.