In this study, a calibrated dual-camera device, a fixed camera and a pan-tilt-zoom camera, is setup to monitor moving vehicles in an open space. This device not only tracks multiple targets but also gets the license plate images with high quality. Next, a convolutional neural network(CNN) is designed to be a detector and a character classifier for efficiently locating the regions of license plates and recognizing the alphabets on them. Two working environments were setup at the entrance of a university and at a pedestrian-only region in campus. Some experimental results are given to show the validity of the proposed approach.