@inproceedings{5c3fe07de44c40a78168ed1f8d897144,
title = "License plate detection and recognition using a dual-camera module in a large space",
abstract = "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.",
keywords = "Convolution neural network, Dualcamera device, License plate detection/recognition, Video surveillance",
author = "Han, {Chin Chuan} and Hsieh, {Cheng Ta} and Chen, {Ying Nong} and Ho, {Gang Feng} and Fan, {Kuo Chin} and Tsai, {Chang Lung}",
year = "2007",
doi = "10.1109/CCST.2007.4373505",
language = "???core.languages.en_GB???",
isbn = "1424411297",
series = "Proceedings - International Carnahan Conference on Security Technology",
pages = "307--312",
booktitle = "Proceedings 2007 41st Annual IEEE International Carnahan Conference on Security Technology, ICCST",
note = "2007 41st Annual IEEE Carnahan Conference on Security Technology, ICCST ; Conference date: 08-10-2008 Through 11-10-2008",
}