Kinship Verification System based on the Color Spaces Analysis

Metric learning has attracted wide attention in face and kinship verification and a number of such algorithms have been presented over the past few years, this system has a number of applications such as organizing collections of images and recognizing resemblances among humans and finding of missing children. In this work , we propose a novel approach based on the Weber Local Descriptor (WLD) with color spaces, and the Multi-Lavel (ML) representation, Moreover, the use of Rank features (TTest) to reduce the number of features and the support vector machine (SVM) for the kinship classification. Our approach consists of six stages which are : (1) Face preprocessing (2) applied the color spaces (3) features extraction using WLD , with face representation , (4) pair features representation, (5) features selection and (6) classification using SVM. The proposed approach istested and analyzed on five publicly available databases (Cornell , UB KinFace, Familly 101, KinFac W-I and W-II).

• kinship verification
• face verification
• color space
• Weber local descriptor
• multi-level representation
• feature selection
• support vector machine

• Face recognition and analysis
• Face and Expression Recognition
• Biometric Identification and Security
• kinship verification
• face verification
• color space
• Weber local descriptor
• multi-level representation
• feature selection
• support vector machine
• Computer Vision and Pattern Recognition
• Signal Processing
• Computer Science