Design and development of a parallelized algorithm for face recognition in mobile cloud environment

Abstract

Face recognition is the biometric application to recognise the identity. Face recognition application holds a set of images which are called databases stored by the user at cloud database. Cloud computing environment, database can be stored in the cloud environment to achieve huge data storage area. The problem with these data storages are that because of that huge size processing on this storage takes too much of compiling time. This paper aims to develop face recognition in mobile cloud environment by exploiting data or task parallelism in existing face recognition algorithms. To design and develop parallel PCA based face recognition algorithm. The parallel PCA face recognition algorithm has been deployed in the cloud server for performing PCA by request of user. It matches the image on the cloud server and gives response back to the user in the fewer amounts of time and with reduced latency. The developed Parallel PCA face recognition algorithm has minimized the overall response time for the face recognition algorithm. The performance of the developed system is tested and analysed on real face images. To analyse the developed system, a centralized and distributed based server methods are developed and comparison is being carried out. The conclusion drawn that the distributed server improves the efficiency as well as the computing power as compared with centralized server system. The comparison of centralized and distributed based servers is carried out by observing the time taken while varying the number of images in the training dataset.