Biometrics and Bioinformatics

R. Nandakumar ¹, K. Prasanth ¹

Affiliations
1 Department of Electronic and Communication, IN

Abstract

Virtualization technology is the base technology used in Cloud computing. Therefore, virtualization enables Cloud computing provide hardware and software services to the users on demand. Actually, many companies migrates to the Cloud computing for many reasons such as capabilities of processor, bus speed, size of storage, memory and managed to reduce the cost of dedicated servers. However, virtualization and Cloud computing contain many security weaknesses that affects the biometric data confidentiality in the Cloud computing. Those security issues are VM ware escape, hopping, mobility, diversity monitoring and etc. Furthermore, the privacy of a particular user is an issue in biometric data i.e. the face reorganization data for a famous and important people. Therefore, this paper proposed biometric encryption to improve the confidentiality in Cloud computing for biometric data. Also, this paper discussed virtualization for Cloud computing, as well as biometrics encryption. Indeed, this paper overviewed the security weaknesses of Cloud computing and how biometric encryption can improve the confidentiality in Cloud computing environment. Apart from this, confidentiality is enhanced in Cloud computing by using biometric encryption for biometric data. The novel approach of biometric encryption is to enhance the biometric data confidentiality in Cloud computing.

Full Text

     

K. Prasanth ¹, G. Vinoth Kumar ¹, P. Jeyaprakash ¹

Affiliations
1 Kathir College of Engineering, Coimbatore, IN

Abstract

Facial expression is the natural means for human beings to show their emotions and motivations. The problem of unconstrained face recognition from remotely acquired images is addressed. When blurring comes to picture, face recognition becomes difficult. The main factors that make this problem challenging are image degradation due to blur and the appearance variations due to illumination and pose. Many of the approaches concentrate mainly on the blurring part alone. A blur-robust face recognition algorithm DRBF (Direct Recognition of Blurred Faces) and IRBF (Illumination-Robust Recognition of Blurred Faces) is proposed in this paper. This algorithm can easily incorporate prior knowledge on the type of blur as constraints. In addition to this, the illumination defects are also considered along with the blur problems. And the features of facial components such as eyes, nose, and mouth in gray images of faces are extracted and the facial expressions are identified.

Keywords

Unconstrained Face Recognition, Remote Biometrics, Direct Recognition of Blurred and Illuminated Faces, Facial Expression and Facial Expression Classifier.

Full Text