Unlike many other biometrics, face recognition is a Passive process that doesn't need the user's cooperation; this characteristic makes the face recognition very valuable for the surveillance and crimes solution purposes.
But there are some drawbacks with face first: the face features are not permanent, it changes over age. Second: It is not accurate for Identical twins.
Some challenges could face the face recognition process like the facial expressions, pose and illumination.
Many researchers tried to develop a face recognition system that overcomes these challenges.
Yue Ming et al., 2010 [] proposed a framework to solve the facial expression problem depending on the structure of faces not on individual points. The authors used a correlative
But there are some drawbacks with face first: the face features are not permanent, it changes over age. Second: It is not accurate for Identical twins.
Some challenges could face the face recognition process like the facial expressions, pose and illumination.
Many researchers tried to develop a face recognition system that overcomes these challenges.
Yue Ming et al., 2010 [] proposed a framework to solve the facial expression problem depending on the structure of faces not on individual points. The authors used a correlative