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- W3129820694 abstract "The recognition of license plates from input images often does not give a complete answer. There might be some characters that are not recognized by a neural network, or there might be more characters recognized then possible on a single plate. Using constraints in the syntax of a license plate it is possible to rule out a number of options, but certainly not all of them. To obtain the correct data from these license plates images an evaluation of the plate geometry is required. The goal in this thesis is to chart all the errors that occur in todays license plate recognition software, and use the results to create a license plate model for geometric matching. By using both geometry and syntax properties found in the dataset and the constraints put on license plate geometry and syntax by regulations an attempt is made to achieve a higher rate of recognition then before." @default.
- W3129820694 created "2021-03-01" @default.
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- W3129820694 date "2003-01-01" @default.
- W3129820694 modified "2023-09-23" @default.
- W3129820694 title "Geometric Model Matching on License Plates" @default.
- W3129820694 hasPublicationYear "2003" @default.
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