An Introduction of Face Recognition and Face Detection for Blurred and Noisy Images

Ratnesh Kumar Shukla¹ , Ajay Agarwal² , Anil Kumar Malviya³

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.3 , pp.39-43, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i3.3943

Online published on Jun 30, 2018

Copyright © Ratnesh Kumar Shukla, Ajay Agarwal, Anil Kumar Malviya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
In this paper the proposed model is using for the identity to the noisy and blurred images. In our surrounding they are a big problem of randomly change the environment, or climate change. Image processing, are working in different platform. Such as Pattern Recognition, Computer vision Pattern, Machine Learning and Artificial Intelligence is using for the authentication of unauthorised person. Images are using for the authentication and verification. Authentication and Registration is the initial step of the identification and verification of the object. In this paper we are introducing blur and noisy images. And compare these images in our database. If images are verified from proposed model then they registered in the database for future use. The problem is obtaining in unclear images. Blur and Noise is the main disturbance of the images found in captured process. This problem obtain when we are capturing the images. They are found in the presence of dust and lighting. So in this technique we are remove the noise and blur of images. In this proposed model for deblur and denoise is work on corrupted images. In current scenario there are different algorithms working on the quality of images. Images are in pixel from and there are found in million colours in images. Then it is found very difficult to original images. When we are using high quality of cameras then it is possible to capture good quality images. But when we are using these novel method, we are if recognize the image. So we are using proposed algorithm to identify the images. We are comparing the trainee images to store our database. Then we found a real image and registered in the database.

Key-Words / Index Term :
Blurred and Noise Image, Wiener Filter, RANSAC algorithm, Face Recognition System, Templates, Data storage

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