Abstract:

The Biometric is the most important feature technique utilize for Human Recognition. It is a time of Computer Technology which deals with Digital Information Technology; every person has some special characteristics which can be utilized for detection and identification. The human detection and recognition is a credential task to recognize person for their activity in social area as well as private secure area. Many researchers have been dealing with different algorithms for Recognition. Specially, Face, Fingerprint, and Retina Scan are processed in the form of Image Information. In computer engineering Images are processed as signal and signal processing is nothing but dealing of pixel values in the form of frequency values. Nowadays PCA (Principle Components based analysis) is the most popular algorithm used for face recognition. In this dissertation we proposed the utilization of PCA in Face Recognition. We have several of the activities which play important role in our life .The quality and movement of image is affected the result.

Keywords: Digital Watermarking, Sustainable Development, Wavelet based Watermarking

Introduction:

In present time two image registration techniques are very popular like surface based image registration and point based image registration. Here we have to introduce about the method which is most effective for face identification. We work on the method which registers the best image (high quality image) for batter results.

The research is done to judge applicability in terms of Peak Signal to Noise Ratio(PSNR) and Correlation Coefficient (CC). The calculated results are compare for the different possibility and dramatic conditions. The comparison is targeted to getthe best quality Image which proves that Image Registration actually improves the performance of Face Recognition by avoiding failure and false results. The application areas of the research work done are: Preliminary Control, Social Media and Movie, Smart Device Identification, Data Security.

Result and discussion:

Digital Signal Processing is only way to get meaning full information and then revert to know values. The Principal Component Analysis (PCA) used Orthogonal Transformation to change correlated variables into uncorrelated variables known as principal components.Basic approach of matching the faces includes the set of initialization operations: First is the acquisition of face images, then calculation of Eigenface (from the train database) occur which keeps only selected images that correspond to the largest eigenvalues. It is a topic which actually relates to the machine learning which then can be utilizing for artificial intelligence. This research work includes a face recognition system improved using image registration method for online conferencing system. This research found two issues:- Front End : User authentication using face recognition for online web conferencing/ webinar. And Back End:  Recognition of blurred or Noisy image (Sometimes Moving Image). The face recognition is possible using principal component analysis of the face image.

Experimental:

The experiment and results are obtained which are then compare with SNR and PSNR values for image quality measurement and co-realation coefficient is tested for similarity measurement. The calculation and comparison of result for the certain parameters (SNR, PSNR, CC, and BCR) for selected variable images proves that image quality after registration method defiantly improves the performance of face recognition system. The overall conclusion of this dissertation work is that the face Recognition using facial feature expression is possible and performance of authentication can be improved by image registration method.

Conclusion:

The principal of communication needs user qualification to access the services and authorization. From the user point of view it is also important to secure ownership of the data as well as account. Many times it is found that user account got hacked of fake user pretend like original user. The face recognition can easily apply on any system based on internet.The futuristic research improvements to the authentication and face recognition policies are as follows: Biometric features like fingerprint recognition can be incorporate to access online account with the combination of face recognition. User validation for online ticket booking management can also be improved by direct matching of faces. Image recognition algorithm can be enhanced by image registration and features matching advanced policies. Civilian registration and validation in many government online services like E-mitra. Government can also utilize these principals to avoid fake voting.

References:

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