Onssi and Vaxtor partner on licence plate recognition integration

Vaxtor Corporation’s (Vaxtor) advanced LPR analytics platform can now be deployed across Onssi’s Ocularis VMS platform to recognise, capture and archive data on licence plates, railway vehicles, US Department of Transport (USDOT) numbers and more, as part of an integration partnership between both companies. The agreement, according to Onssi’s Ken LaMarca, VP of sales & marketing, allows the solution to deliver a range of security and operations data to meet the specific challenges of the transportation and
June 26, 2018 Read time: 2 mins

Vaxtor Corporation’s (Vaxtor) advanced LPR analytics platform can now be deployed across 677 Onssi’s Ocularis VMS platform to recognise, capture and archive data on licence plates, railway vehicles, US Department of Transport (USDOT) numbers and more, as part of an integration partnership between both companies. The agreement, according to Onssi’s Ken LaMarca, VP of sales & marketing, allows the solution to deliver a range of security and operations data to meet the specific challenges of the transportation and law enforcement markets.

The Vaxtor LPR solutions include the capture of OCR, MMR (year, make and model of vehicles), USDOT, railway, container, red light and wrong turn detection integrations. The analytics are said to recognise letters, numbers and symbols both vertically and horizontally. Ocularis is available as a professional model for organisations operating multiple locations with small to mid-sized camera counts as well as an Enterprise version for a range of mid to large IT-centric companies. In addition, the Ultimate model is aimed at large clients with extended command and control needs and recording server failover.

For more information on companies in this article

Related Content

  • IR’s invisible benefit for traffic surveillance and enforcement
    June 30, 2016
    Advances in vision technology are enhancing traffic surveillance and enforcement applications. Variable lighting conditions have long been a stumbling block for vision technology applications in the transport sector. With applications such as ANPR, the read-rate may vary between daylight and night and can be adversely affected by glare and low sun. Madrid, Spain-based Lector Vision had these considerations in mind when designing its Traffic Eye ANPR system, which combines off-the-shelf and custom hardware
    Read More
  • Videalert provides full time enforcement with part time workload
    March 19, 2014
    Videalert says its algorithms on automated enforcement can reduce the workload on staff while providing an effective deterrent to offenders. Colin Sowman reports. While members of the public may believe that the enforcement of parking regulations, bus lanes and box junctions has no practical benefit and is purely a money-making operation, for many authorities the opposite is true. Enforcement is a loss-making but vital exercise as illegally parked vehicles create obstructions and dangers leading to gridl
    Read More
  • Xerox automates HOV/HOT enforcement
    May 27, 2014
    Counting the number of people in a vehicle has always been a manual task, but now Xerox has developed a real-time system to automate the process. Xerox has introduced an automated system that determines the number of passengers in a vehicle, enabling authorities to detect non-qualifying drivers using the High Occupancy Vehicle (HOV) and High Occupancy Toll (HOT) lanes. Traditionally HOV/HOT enforcement has entailed local police visually confirming each vehicle has the required number of occupants and chasin
    Read More
  • USDoT pilots show win-win potential for connected vehicles
    December 19, 2017
    Pete Goldin discovers the state of play with connected vehicles trials in the US and the impact of Hurricane Irma on Tampa’s pilot. The US Department of Transportation’s (USDoT’s) connected vehicle (CV) pilot sites have moved into phase 2 of the deployment programme– design, build, test and, maybe most importantly, collaborate.
    Read More

Highlighted Content