Kinship Verification based on Local Binary Pattern features coding in different color space

Kinship verification is one of the interesting and challenging topics which is related to face analysis. Most of existing methods have been trying to find out the relevant information between two persons (edge nose, lip, eyes) to increase the verification rate. In this paper, we propose to apply the Local Binary Pattern for Kinship on different color space. Then the features are computed by $\chi^{2}$ distance and apply feature selection to reduce the noisy and irrelevant features. The Support Vector Machine is used to train and predict the model. We analyze the effectiveness of our method by carrying out experiments on two popular databases such as KinFaceW-I and KinFaceW-II.