LPQ and LDP Descriptors with ML Representation for Kinship verification
The automatic verification of kinship is a challenging problem that recently attracted much interest in computer vision, the kinship verification has become an active research field due to its potential applications such as organizing photo albums and images annotation, recognizing resemblances among humans and finding of missing children. In this paper, we propose an approach which takes two images as an input then give kinship result (kinship non kinship) as an output.This approach based on the Local Phase Quantization (LPQ) and Local directional pattern (LDP) features descriptors and the ML (Multi Level) representation for the kinship verification from facial images, this work consists six stages which are (i) face preprocessing, (ii) features extraction, (iii) face representation (iv) pair features representation and normalization, (v) features selection and (vi) kinship verification. Experiments are conducted on four public databases (Cornell KinFace, UB Kin database, KinFace I, and KinFace II) The obtained results are good compared with state of the art approaches.