Abstract
This paper introduces an auto-calibration mechanism for an Automatic Number Plate Recognition camera dedicated to a vehicle speed measurement. A calibration task is formulated as a multi-objective optimization problem and solved with Non-dominated Sorting Genetic Algorithm. For simplicity a uniform motion profile of a majority of vehicles is assumed. The proposed speed estimation method is based on tracing licence plates quadrangles recognized on video frames. The results are compared with concurrent measurements performed with piezoelectric sensors.
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Notes
- 1.
By the term roughly calibrated it is meant that a camera is mounted at its desired location, it points at the road and its focal length is vaguely set with a bare eye such that number plates are readable on the captured images.
- 2.
Infinitely-distant points of the 3D space correspond to \(s = 0\) which make them invisible in the image space.
- 3.
The notations of \(x^{(\cdot )}\) and \(y^{(\cdot )}\) were introduced in Sect. 4.
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Filipiak, P., Golenko, B., Dolega, C. (2016). NSGA-II Based Auto-Calibration of Automatic Number Plate Recognition Camera for Vehicle Speed Measurement. In: Squillero, G., Burelli, P. (eds) Applications of Evolutionary Computation. EvoApplications 2016. Lecture Notes in Computer Science(), vol 9597. Springer, Cham. https://doi.org/10.1007/978-3-319-31204-0_51
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DOI: https://doi.org/10.1007/978-3-319-31204-0_51
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