Facial Kinship Verification in Forensic Investigation Using Deep Neural Networks

الملخص

The human face contains a wealth of information that is influenced by genetics. Family members often share common facial characteristics due to their shared genetic makeup. By comparing the facial features of individuals, forensic investigators can examine the degree of similarity and infer their kinship. Kinship verification provides a powerful tool in forensic investigations, contributing to the resolution of missing person cases, social media analysis, genealogy research, and historical study. The research problem is verifying if two people have a kinship by analyzing two face images together, extracting the relationship features between them, and then determining if they have Kin or not. A Kinship Verification model is proposed using a three-Dimensional Convolutional Neural Network.  This work consists of the following stages: the preprocessing stage and the kinship verification stage, and each stage includes multiple steps that perform different functions. In the preprocessing stage, the input images are prepared to be suitable for deep neural network model by extract ROI, scaling, and normalizing them. The kinship verification stage is implemented to provide the kinship decision in two steps: the feature extraction step and then classification step to decide on those images: kin or not. Extensive experiments revealed promising results compared with many state-of-the-art approaches. The accuracy of the proposed system reached 92.25% in the KinFaceW-I dataset and 95.25%in the KinFaeW-II dataset.