Cities & public sector · Case study
Vehicle and plate regions became validated events despite difficult image conditions.
Case study context
An urban camera project needed to convert passing vehicles into structured observations that included a validated plate candidate. A complete street image could contain several vehicles, signs, advertisements and road markings, so optical character recognition could not know which text belonged to a plate. The plate itself might also be small, angled, blurred, partly hidden or badly exposed.
The pipeline first detected and tracked a vehicle across frames, then localized and normalized its plate region. Character recognition ran only on that focused evidence, allowing the system to prefer useful frames, validate the candidate and emit a structured event with its quality state and source context.
Frame-to-event evidence
Use the controls below to inspect the key stages, constraints and validation decisions in that process.
Track V-047Plate regionEvidence retained: Every event retained the source frame, selected vehicle track, plate crop, recognition candidate and quality state.
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