Vehicle number plate recognition systems are expected to have numerous applications in traffic surveying and monitoring, e.g. finding stolen cars, controlling access to car parks and gathering traffic flow statistics. The Computer Vision Group at the University of Tras-os-Montes e Alto Douro, in collaboration with the Universities of Aveiro and Bristol, has been developing a number plate reading system [3][4][5]. The system builds on the experience gained by the Computer Vision Group at the University of Bristol while developing previous transputer based prototypes [~1[~1[81[121.The main tasks of a number plate recognition system are the location of the number plate area in the image, the segmentation of the characters and their identification. These tasks are strongly inter-related, mainly because the way to check if the number plate has been correctly located is based on the result of the character identification process (it should correspond tal a predefined syntax). Algorithmic improvements to previons versions of the system, based on the results of intensive testing, are described in the paper. Por the location of the number plate area in the image, a new line-based method has been developed. The method, instead of looking for character like shapes in the image, takes advantage of the "signature" of the number plate area in a horizontal cross-section of the image. The method used for the segmentation of the characters is derived from a technique first proposed by Lu [SI. The identification of the characters uses the OCIt engine developed by Barroso et a1 [3][4], based on the critical points method [10][11].

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