Title :
Scale-Invariant Feature Extraction by VQ-Based Local Image Descriptor
Author :
Chen, Qiu ; Kotani, Koji ; Lee, Feifei ; Ohmi, Tadahiro
Author_Institution :
New Ind. Creation Hatchery Center, Tohoku Univ., Sendai, Japan
Abstract :
SIFT (scale invariant feature transform) feature is identified as being invariant to common image deformations caused by the rotation, scaling, and illumination. In this paper, instead of using SIFT´s smoothed weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for local image descriptor. Experimental results demonstrate that the VQ-based local descriptors are more robust to image deformations.
Keywords :
feature extraction; image coding; vector quantisation; image deformations; local image descriptor; scale invariant feature transform; scale-invariant feature extraction; vector quantization histogram; Electronics industry; Face recognition; Feature extraction; Histograms; Image coding; Industrial electronics; Lighting; Object recognition; Robustness; Vector quantization; Local descriptor; SIFT feature; Vector quantization histogram;
Conference_Titel :
Computational Intelligence for Modelling Control & Automation, 2008 International Conference on
Conference_Location :
Vienna
Print_ISBN :
978-0-7695-3514-2
DOI :
10.1109/CIMCA.2008.134
