A new method color MS-BSIF Features learning for the robust kinship
  verification
Rachid Aliradi Abdealmalik Ouamane Abdeslam Amrane
the paper presents a new method color MS-BSIF learning and MS-LBP for the
kinship verification is the machine's ability to identify the genetic and blood
the relationship and its degree between the facial images of humans. Facial
verification of kinship refers to the task of training a machine to recognize
the blood relationship between a pair of faces parent and non-parent
(verification) based on features extracted from facial images, and determining
the exact type or degree of this genetic relationship. We use the LBP and color
BSIF learning features for the comparison and the TXQDA method for
dimensionality reduction and data classification. We let's test the kinship
facial verification application is namely the kinface Cornell database. This
system improves the robustness of learning while controlling efficiency. The
experimental results obtained and compared to other methods have proven the
reliability of our framework and surpass the performance of other
state-of-the-art techniques.