• Dr. Himani Mittal Gupta
• Stuti Aggarwal

In this project a novel method based on facial skin aging features and Artificial Neural Network (ANN) is proposed to classify the human face images into three age groups –child©, adult(a) and old(o). Face images are being increasingly used as additional means of authentication in applications of high security zone. The facial skin aging features are extracted by using HAAR transform. And explicit use of PCA and HOG techniques is involved. In our project, effective age group estimation is done using face features like texture and shape of human face. For better performance, it uses two types of features namely, geometrical features and wrinkle features and it includes three main iterations: Pre processing, Feature extraction (using HAAR technique) and Classification(using ANN classifier).As the age of an individual increases, the facial features changes and the database of the security system needs to be updated at regular intervals of time which is a cumbersome task. So, in this project we have addressed the issue of facial aging and have come up with a solution that identifies a person in spite of aging. The geometrical features of facial image includes wrinkle geography, face angle, left to right eye distance, eye to nose distance, eye to chin distance and eye to lip distance. And Viola Jones technique is used for face detection

Network on Chip (NoC); Heterogeneous Reconfigurable Router; Buffer; Latency; Power dissipation; Register Transfer Level (RTL) Design, Low Power, Low Area , Throughput ,Latency ,Critical time path.

"AI technique for resolving security in highly sensitive domain in automated face recognition system using Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.559-562, June 2019, Available :http://www.jetir.org/papers/JETIR1907540.pdf

"AI technique for resolving security in highly sensitive domain in automated face recognition system using Artificial Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp559-562, June 2019, Available at : http://www.jetir.org/papers/JETIR1907540.pdf