A Multi-User Face Identification system with distributed tasks in a Big Data Environment

Computer vision is a field that handles how a computer can gain a high level of understanding from several kind of inputted information. In general, it tries to automate tasks that humans have the ability to do. Computer vision tasks contain a method to understand digital images and extract high dimensional in order to generate a piece of symbolic information, for example, in the forms of decisions. One of the open issues in image processing and computer vision nowadays is how we can handle the problem of quick identification in a multi-user identification system. In this paper, We propose an identification system in a big data environment that provide and an acceptance identification time while keeping a good performance, in uncontrolled conditions, in comparison with some compared classical systems.