A Comprehensive Unconstrained, License Plate Database

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Abstract

In this paper, information about a large and diverse database of license plates from countries around the world is presented. CENPARMI’s growing database contains images of isolated plates, including a small percentage of vanity plates, as well as landscapes, where the vehicle is included in the image. Many images contain multiple license plates, have complex scenery, have motion blur, and contain high light and shadow contrast. Photos were taken during seasons, many are occluded by foreground objects, and some were taken through mist, fog, snow, and/or glass. In many cases, the license plate, camera, or both were in motion. In order to make training more robust, different cameras, lenses, focal lengths, shutter speeds, and ISOs were used. A summary of proposed guidelines used for license plate design are outlined, details about the database of license plates are presented, followed by suggestions for future work.

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Nobile, N., Chan, H. K. P., & Blom, M. (2020). A Comprehensive Unconstrained, License Plate Database. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12068 LNCS, pp. 555–561). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59830-3_48

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