A REVIEW OF FACE RECOGNITION

International Journal of Advanced Computer Science and Applications, 2018

With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. In this survey paper, we have tried to address most endeavoring face features such as pose invariance, aging, illuminations and partial occlusion. They are considered to be indispensable factors in face recognition system when realized over facial images. This paper also studies state of the art face detection techniques, approaches, viz. Eigen face, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, Elastic Bunch Graph Matching, 3D morphable Model and Hidden Markov Models. In addition to the aforementioned works, we have mentioned different testing face databases which include AT & T (ORL), AR, FERET, LFW, YTF, and Yale, respectively for results analysis. However, aim of this research is to provide comprehensive literature review over face recognition along with its applications. And after in depth discussion, some of the major findings are given in conclusion.

2017

Face recognition has been challenging and interesting area in real time applications. Face recognition is a form of biometric identification that relies on data acquired from the face of an individual. A large number of face recognition along with their modifications, have been developed during the past decades. Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. In real world applications, it is desirable to have a stand-alone, embedded facerecognition system. The reason is that such systems provide a higher level of robustness,hardware optimization, and ease of integration. In this paper an attempt is made to review a wide range of methods used for face recognition comprehensively. This include PCA, ICA, LDA, SVM, Gabor wavelet soft computing tool like ANN for recognition, LBP and various hybrid combination ...

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019

Face recognition has been a quickly developing, testing and intriguing region progressively applications. An extensive number of face recognition calculations have been produced in a decade ago. In this paper an endeavor is made to survey an extensive variety of techniques utilized for face recognition exhaustively. This incorporate PCA, LDA, ICA, SVM, Gabor wavelet delicate registering instrument like ANN for recognition and different cross breed blend of this systems. This audit examines every one of these techniques with parameters that difficulties face recognition like illumination, pose variation, facial expressions.

Face recognition is considered as one of the emerging topics in computer vision application. Currently biometric research is mainly focused on automated face recognition in various applications such as surveillance application in various public security measures. Face recognition is a biometric system used to categorize or authenticate a person from a digital image by extracting its features and then distinguishing it, regardless external conditions. This learning version has mainly two motives: first one is the extensive assortment of profitable and regulation implementation claims, second is the convenience of possible skills. This paper is organised as three sections. The first section describes brief introduction to face recognition. The second section types of face recognition and various problems affecting the process and finally third section describes a comparative study of different face recognition methods.

Face recognition has been a fast growing, challenging and interesting area in real time applications. A large number of face recognition algorithms have been developed in last decades. In this paper an attempt is made to review a wide range of methods used for face recognition comprehensively. This include PCA, LDA, ICA, SVM, Gabor wavelet soft computing tool like ANN for recognition and various hybrid combination of this techniques. This review investigates all these methods with parameters that challenges face recognition like illumination, pose variation, facial expressions.

International Journal of Engineering Research and Technology (IJERT), 2014

https://www.ijert.org/comparative-study-of-face-recognition-techniques https://www.ijert.org/research/comparative-study-of-face-recognition-techniques-IJERTV3IS030687.pdf The aim of this paper is to compare various methods for face recognition. In this paper we are going to discuss various techniques for face recognition. This paper includes a brief description of PCA (Principle Component Analysis), LDA (Linear Discriminant Analysis), LBP (Local Binary Pattern), Gabor filter, LGBP (Local Gabor Binary Pattern). Comparative study of various methods is discussed in this paper and from this study a suitable and more efficient technique is found out which will give more effective result.

International Journal of Computer Applications, 2015

In recent years, the biometrics has achieved a great attention on a world level. A Biometric System operates by getting biometric information from a personal that extracts a feature set from the data which is acquired, and helps in comparing this feature set against the template stored in the database. There are biometric technologies which could either be physiological or behavioral. Face Recognition is having the importance to provide biometric authentication with easy image acquisition that can be used for online and offline applications. There are number of existing approaches for biometric facial recognition and classification. This paper gives a review on some of the common and reliable approaches which include PCA, LDA, SVM, SIFT, SURF, etc.

2018

Face Recognition which is still one of the challenging topic in Computer Vision and Image Processing field remains an open problem as the recent advancements has not yet reached high recognition performance in real world environment. With the usage of technologies for Computer Vision and Image Processing, Face Recognition has gained more interest due to it applications and concerns on high security. Human Face can be considered as a key identifier in various fields and Computational models of face recognition can be applied to a wide variety of problems involving security system, Identification of criminals or suspects, image and film processing, and human computer interaction. This field of computer vision and image processing involves recognition of face from image or a video source. Several algorithms and methodologies for face identification have been developed having their own pros and cons. In this paper, we will provide review and survey of some famous major face recognition ...

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019

Face recognition has now become one of the interesting fields of research and has received a substantial attention of researchers from all over the world. Face recognition techniques has been mostly used in the discipline of image analysis, image processing, etc. One of the face recognition techniques is used to develop a face recognition system to detect a human face in an image. In face recognition system a digital image with a human face is given as an input which extracts the significant features of face such as (eyes, nose, chin, cheeks, etc) to recognize a face in a digital image which is an exhausting task. Security of information is very salient feature and is difficult to achieve. Security cameras are present in offices, universities, banks, ATMs, etc. All these security cameras are embedded with face recognition systems. There are various algorithms which are used to solve this problem. This paper provides an overview of various techniques which are often used for this face recognition in a face recognition system. This paper is divided into five parts, first section concludes various face detection techniques, second section describes about image processing ,third section have details about face recognition techniques, fourth section describes various classification methods and last section concludes all of these sections.

— Face recognition has been a fast emergent and exciting area in real time applications. Automatic face recognition has shown great achievement for high-quality images under embarrassed conditions. In this paper techniques of Face detection along with Face Recognition are discussed. Human and object frames, background frames are separated by implementing a face detection algorithms like Viola-Jones & Skin Detection algorithms. In this paper we have discussed, analysed, & compare some popular face detection methods like PCA, LDA, PCA + LDA Hybridization and Gabor wavelet transformations and also tried to attempt a comparative study of these methods.