29-10-2013, 11:42 AM
COLOR LOCAL TEXTURE FEATURES FOR COLOR FACE%0ARECOGNITION.pdf (Size: 89.99 KB / Downloads: 16)
COLOR LOCAL TEXTURE FEATURES FOR COLOR FACE
RECOGNITION
This paper proposes new color local texture features, i.e., color local
Gabor wavelets (CLGWs) and color local binary pattern (CLBP), for
the purpose of face recognition (FR).
The proposed color local texture features are able to exploit the
discriminative information derived from spatiochromatic texture
patterns of different spectral channels within a certain local face
region.
Furthermore, in order to maximize a complementary effect taken by
using both color and texture information, the opponent color texture
features that capture the texture patterns of spatial interactions
between spectral channels are also incorporated into the generation of
CLGW and CLBP.
In addition, to perform the final classification, multiple color local
texture features (each corresponding to the associated color band) are
combined within a feature-level fusion framework.
Extensive and comparative experiments have been conducted to
evaluate our color local texture features for FR on five public face
databases, i.e., CMU-PIE, Color FERET, XM2VTSDB, SCface, and
FRGC 2.0. Experimental results show that FR approaches using color
local texture features impressively yield better recognition rates than
FR approaches using only color or texture information.
Particularly, compared with grayscale texture features, the proposed
color local texture features are able to provide excellent recognition
rates for face images taken under severe variation in illumination, as
well as for small- (low-) resolution face images. In addition, the
feasibility of our color local texture features has been successfully
demonstrated by making comparisons with other state -of-the-art color
FR methods.
Abstract of the Project
Proposed System Advantages
Architecture Diagram
Block Diagram
Explanation of Block Diagram
Components usage Details