Identifying Resemblance in Local Plastic Surgical Faces Using Near Sets for Face Recognition

In recent years, much advancement have been made in face recognition techniques which leads to the popularity of plastic surgery procedures. Pose, illumination and expressions are some of the problems that have been already recognized and studied in the domain of face recognition. In this paper, we have proposed an approach based on near set theory to develop a classifier for facial images that have previously undergone some feature modifications through plastic surgery. Our work concerns only geometrically obtained feature values and their approximation using near sets. Near set theory provides a method to establish resemblance between objects contained in a disjoint set, that is, it provides a formal basis for observation, comparison and classification of the objects. The experimental results indicate the performance and accuracy of the plastic surgery based face recognition.