Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 20th IEEE International Conference on Image Processing (ICIP), 2013 |
| Place of Publication | Australia |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 4210-4214 |
| ISBN (Print) | 9781479923410 |
| DOIs | |
| Publication status | Published - Sep 2013 |
| Event | 20th IEEE International Conference on Image Processing - Melbourne, Australia, Melbourne, Australia Duration: 15 Sep 2013 → 18 Sep 2013 |
Conference
| Conference | 20th IEEE International Conference on Image Processing |
|---|---|
| Abbreviated title | ICIP |
| Country | Australia |
| City | Melbourne |
| Period | 15/09/13 → 18/09/13 |
Fingerprint
Cite this
}
Derivative Variation Pattern for Illumination-Invariant Image Representation. / Tavakolian, M.; Hajati, F.; Mian, Ajmal; Gao, Y.; Gheisari, S.
Proceedings of 20th IEEE International Conference on Image Processing (ICIP), 2013. Australia : IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 4210-4214.Research output: Chapter in Book/Conference paper › Conference paper
TY - GEN
T1 - Derivative Variation Pattern for Illumination-Invariant Image Representation
AU - Tavakolian, M.
AU - Hajati, F.
AU - Mian, Ajmal
AU - Gao, Y.
AU - Gheisari, S.
PY - 2013/9
Y1 - 2013/9
N2 - This paper presents a novel image descriptor called Derivative Variation Pattern (DVP) and its application to face and palmprint recognition. DVP captures image variations in both the frequency and the spatial domains. The effects of uncontrolled illumination are compensated in the frequency domain by discarding the illumination affected frequencies. Image pixels are encoded as binary patterns based on the higher-order spatial derivatives computed in the spatial domain. The proposed descriptor was evaluated on the Extended Yale-B and FERET face databases, and the PolyU palmprint database. Experimental results demonstrate the effectiveness of the DVP descriptor in both the face and the palmprint recognition tasks under uncontrolled illuminations.
AB - This paper presents a novel image descriptor called Derivative Variation Pattern (DVP) and its application to face and palmprint recognition. DVP captures image variations in both the frequency and the spatial domains. The effects of uncontrolled illumination are compensated in the frequency domain by discarding the illumination affected frequencies. Image pixels are encoded as binary patterns based on the higher-order spatial derivatives computed in the spatial domain. The proposed descriptor was evaluated on the Extended Yale-B and FERET face databases, and the PolyU palmprint database. Experimental results demonstrate the effectiveness of the DVP descriptor in both the face and the palmprint recognition tasks under uncontrolled illuminations.
U2 - 10.1109/ICIP.2013.6738867
DO - 10.1109/ICIP.2013.6738867
M3 - Conference paper
SN - 9781479923410
SP - 4210
EP - 4214
BT - Proceedings of 20th IEEE International Conference on Image Processing (ICIP), 2013
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - Australia
ER -