Abstract:
Detecting a speed violation of a vehicle traveling from a first roadside system to a second roadside system comprises: protecting evidence data collected at two roadside systems by encrypting each set of data with random session keys at each roadside system, and then encrypting the random session keys with a public key generated from an identity that may include a vehicle identifier and a timestamp. A ratio of the public keys is calculated and used to detect a violation, whereupon a private key is obtained for decrypting at least one of the encrypted session keys, and decrypting at least one of the encrypted evidence data with the decrypted session key.
Abstract:
Detecting a speed violation of a vehicle traveling from a first roadside system to a second roadside system comprises: protecting evidence data collected at two roadside systems by encrypting each set of data with random session keys at each roadside system, and then encrypting the random session keys with a public key generated from an identity that may include a vehicle identifier and a timestamp. A ratio of the public keys is calculated and used to detect a violation, whereupon a private key is obtained for decrypting at least one of the encrypted session keys, and decrypting at least one of the encrypted evidence data with the decrypted session key.
Abstract:
A method is disclosed for reading license plate numbers in a road network, comprising: recording an image of a license plate number at a first location, OCR-reading a license plate character string in the image, and storing an OCR data set in a database; recording an image of a license plate number at a second location, OCR-reading a license plate number character string in the image, and generating a current OCR data set; and, if a confidence measure of the current OCR data set falls below a first minimum confidence value, selecting a stored OCR data set with a license plate number image having a similarity exceeding a minimum similarity value and/or having the greatest similarity to the license plate number image of the current OCR data set, and using the selected OCR data set for improving the license plate number character string of the current OCR data set.
Abstract:
Methods and devices are provided for recording images of vehicles that pass through a section between an entrance and an exit at excessive speed, comprising the following steps: capturing an entry time of a vehicle at the entrance, generating a unique object identifier for the vehicle and storing the entry time under the object identifier; tracking the movement of the vehicle, which is being continuously referenced by way of the object identifier, over the entire section using a sensor arrangement; capturing an exit time of the vehicle that is referenced by way of the object identifier at the exit; and if a comparison of the captured exit time to the stored entry time indicates a speed that exceeds a threshold value: determining an entry image stored under the object identifier or creating an exit image of the vehicle.
Abstract:
A method is disclosed for reading license plate numbers in a road network, comprising: recording an image of a license plate number at a first location, OCR-reading a license plate character string in the image, and storing an OCR data set in a database; recording an image of a license plate number at a second location, OCR-reading a license plate number character string in the image, and generating a current OCR data set; and, if a confidence measure of the current OCR data set falls below a first minimum confidence value, selecting a stored OCR data set with a license plate number image having a similarity exceeding a minimum similarity value and/or having the greatest similarity to the license plate number image of the current OCR data set, and using the selected OCR data set for improving the license plate number character string of the current OCR data set.
Abstract:
Methods and devices are provided for recording images of vehicles that pass through a section between an entrance and an exit at excessive speed, comprising the following steps: capturing an entry time of a vehicle at the entrance, generating a unique object identifier for the vehicle and storing the entry time under the object identifier; tracking the movement of the vehicle, which is being continuously referenced by way of the object identifier, over the entire section using a sensor arrangement; capturing an exit time of the vehicle that is referenced by way of the object identifier at the exit; and if a comparison of the captured exit time to the stored entry time indicates a speed that exceeds a threshold value: determining an entry image stored under the object identifier or creating an exit image of the vehicle.