CIS: an automated criminal identification system

Abstract

The identification of criminals and terrorists is a primary task for police, military and security forces. The terrorist activities and crime rate had increased abnormally. Combating them is a challenging task for all security departments. Presently, these departments are using latest technologies. But they have not enough efficient and accuracy as they expected This research study is based on the analysis of faces, emotions, Ages and genders to identify the suspects. Face recognition, emotion, age and gender identifications are implemented using deep learning based CNN approaches. Suits identification is based on LeNet architecture. In the implementation phase for the classification purpose, Keras deep learning library is used, which is implemented on top of Tensorflow. IMDb is the dataset used for the whole training purpose. Training is performed using in AWS cloud which is more powerful and capable way of training instead of using local machines. Real-time Video and images are taken for the experiment. Results of the training and predictions are discussed below in brief.