A review on surgically altered face images recognition using multimodal bio-metric features

The increasing acceptability of the face as a biometric for recognition is due to the fact that it is non-intrusive. The task of successfully matching face images obtained before and after plastic surgery is a exigent problem. The extent to which a face is altered depends on the form and number of plastic surgeries performed, and it is complex to model these variations. Existing approaches use education based methods that are either computationally costly or rely on a set of training images. Altering facial appearance using surgical procedures has raised a challenge for face recognition algorithms. These procedures alter the facial features and skin texture thereby providing a makeover in the appearance of face. This paper focuses on analyzing the effect of plastic surgery in face recognition algorithms and a multimodal bio-metric feature extractor algorithm is proposed therefore to match face images before and after plastic surgery.