Open AccessFacial Spots Detection Using Convolution Neural Network
Author(s) -
Payal Bose,
Samir Kumar Bandyopadhyay
Publication year - 2020
Publication title -
asian journal of research in computer science
Language(s) - English
Resource type - Journals
ISSN - 2581-8260
DOI - 10.9734/ajrcos/2020/v5i330146
Subject(s) - computer science , face (sociological concept) , artificial intelligence , biometrics , convolutional neural network , face detection , pattern recognition (psychology) , convolution (computer science) , authentication (law) , computer vision , facial recognition system , artificial neural network , computer security , social science , sociology
Nowadays security became a major global issue. To manage the security issue and its risk, different kinds of biometric authentication are available. Face recognition is one of the most significant processes in this system. Since the face is the most important part of the body so the face recognition system is the most important in the biometric authentication. Sometimes a human face affected due to different kinds of skin problems, such as mole, scars, freckles, etc. Sometimes some parts of the face are missing due to some injuries. In this paper, the main aim is to detect a facial spots present in the face. The total work divided into three parts first, face and facial components are detected. The validation of checking facial parts is detected using the Convolution Neural Network (CNN). The second part is to find out the spot on the face based on Normalized Cross-Correlation and the third part is to check the kind of spot based on CNN. This process can detect a face under different lighting conditions very efficiently. In cosmetology, this work helps to detect the spots on the human face and its type which is very helpful in different surgical processes on the face.