Abstract
Multiple Face Detection may be a process of identifying or recognizing quite one face on a picture. Face detections have recently attracted increasing interests thanks to the multitude of applications that end in format. There are numerous methods for identifying the face on the image but here we are using ‘Haar-AdaBoost’, ‘LBP-AdaBoost’, and ‘Neural Networks’ for identifying the faces on the image. And also we are comparing each of the methods to urge which method is giving highly accurate results and which method is giving results very quickly. In humans, by seeing the positions of Eyes, Nose, and Mouth another person can identify the face. The neural mechanism within the brain controls these all and provides the result. We are implementing an equivalent concept on the machine so that the machine can identify the faces by using the positions of the Eyes, Nose, and Mouth. The machine will identify quite one face or multiple faces within the image by using this, and that we also can compare which algorithm will provide a good percentage of accurate results.
Shitharth Selvarajan
Lecturer in Cyber Security
My research interests include Cyber Security, Blockchain, Critical Infrastructure & Systems, Network Security & Ethical Hacking.