Automatic recognition of people is a challenging problem which has received much attention during the recent years [FRHomepage, AFGR, AVBPA] due to its potential applications in different fields such as law enforcement, security applications or video indexing. Face recognition is a very challenging problem and up to date, there is no

Abstract—Advancement and affordability is leading to popularity of plastic surgery procedures. Facial plastic surgery can be reconstructive to correct facial feature anomalies or cosmetic to improve the appearance. Both corrective as well as cosmetic surgeries alter the original facial information to a great extent thereby posing a great challenge for face recognition algorithms. The contribution of this research is (i) preparing a face database of 900 individuals for plastic surgery, and (ii) providing an analytical and experimental underpinning of the effect of plastic surgery on face recognition algorithms. The results on the plastic surgery database suggest that it is an arduous research challenge and the current state-of-art face recognition algorithms are unable to provide acceptable levels of identification performance. Therefore, it is imperative to initiate a research effort so that future face recognition systems will be able to address this important problem. Index Terms—Face recognition, Plastic surgery. I.

A multimodal biometric authentication system based on plastic surgery face image using text dependent speech signal is described in this paper. In addition, the system is designed to keep the rate as high as possible for the plastic surgery face image by using text dependent speech signal. Each module of the system, i.e. the face and speech, is developed separately and fusion is done at matching level to obtain the optimal score for the multimodal biometric recognition system. Although information fusion in a multimodal system can be performed at various levels, integration at the matching score level is the most common approach due to the ease in accessing and combining the scores generated by different matchers. Since the matching scores output by the various modalities are heterogeneous, score normalization is needed to transform these scores into a common domain, prior to combining them.

In recent days, the need of biometric security system is heightened for providing safety and security against terrorist attacks, robbery, etc. The demand of biometric system has risen due to its strength, efficiency and easy availability. One of the most effective, highly authenticated and easily adaptable biometric security systems is facial feature recognition. This paper h a s covered almost all the techniques for face recognition approaches. It also covers the relative analysis between all the approaches which are useful in face recognition. Consideration of merits and demerits of all techniques is done and recognition rates of all the techniques are also compared.

This article introduces perceptual resemblance of plastic surgery facial images using near sets. Near sets are disjoint sets that resemble each other. Near sets facilitate measurement of similarity between objects (digital images) based on features values (obtained by probe functions) that describe the objects. Resemblance between disjoint sets occurs whenever there are observable similarities between the objects in the sets. Each list of feature values defines an object’s description. Objects that are perceived as similar based on their descriptions are grouped together. These groups of similar objects can provide information and reveal patterns about objects of interest in the disjoint sets. The practical application of near set theory on the pre and post plastic surgery facial images to extract resemblance between them was introduced in this article. Facial plastic surgery can be reconstructive to correct facial feature anomalies or cosmetic to improve the appearance. Both corrective as well as cosmetic surgeries alter the original facial information to a great extent thereby posing a great challenge for face recognition algorithms. The main aim of this article is to measure the degree of resemblance of facial images before and after plastic surgery. Blepharoplasty (Eyelid surgery) and Rhinoplasty (Nose surgery) is being considered for this research work due to the maximum number of individuals and easy to differentiate faces before and after plastic surgery.tHD,tNM and tHM is being used to measure the degree of resemblances between plastic surgery images. tHD measure shows around 100 % nearness as compared to tNM and tHM for all features. These measures can also be used in increasing the efficiency of any face recognition system containing plastic surgery images.