Skip to main content

Q-Free neural networks see all sides

Analytics solution extends Intrada ALPR suite
By David Arminas June 2, 2020 Read time: 2 mins
A black and white case: Q-Free also identifies vehicle class, colour, make and model (© Skovalsky | Dreamstime.com)

Q-Free says it is developing improved vehicle analytics and detection for its automatic licence plate recognition (ALPR) technology that identifies vehicle class, colour, make and model.

The technology also identifies which side of the vehicle is being analysed, according to Q-Free.

The vehicle analytics feature is an extension of the Norway-based company’s Intrada ALPR which processes more than a billion licence plates around the globe each day.

The solution can be used with any vendor, making it a convenient extension that opens new possibilities for its customers’ operations and business models.

There is no need for a customer to change existing video infrastructure or invest in costly hardware-based alternatives such as radar and laser, says Q-Free.

The company says that data from test sites in South America and Asia show surveillance and security operators successfully gathering additional identifying characteristics to make the best use of existing video detection equipment.

In particular, the vehicle angle feature determines which side of the vehicle is facing the camera, for example the front or rear. This is helpful in determining entry and exit points in parking applications.

The new vehicle analytics are a result of innovative, reliable neural networks and the company’s machine learning capabilities, according to Marco Sinnema, product manager for Q-Free’s Intrada ALPR library.

“Work with initial customers continues to train the detection of the neural networks – which is now available in our commercial, off-the-shelf Intrada ALPR library,” he said.

“Early results are showing the system performing with great precision, and we plan on delivering the same unrivalled automation accuracy and low error rates offered in our existing ALPR solutions.”

Q-Free’s other products and brands include Intelight, OpenTMS, Intrada, ParQSense and Q-Free Hub.

For more information on companies in this article

Related Content

  • Detection analysis technology successfully predicts traffic flows
    February 3, 2012
    David Crawford investigates new detection analysis technology from IBM. Locations on both the East and West Coasts of the US are scheduled for early deployments of IBM's new Traffic Prediction Tool (TPT) statistical analysis model for the fine-time resolution and near-term prediction of road flow conditions. Developed by IBM's Watson Research Laboratories, TPT is designed to analyse data from the the key detection indicators - average vehicle volumes and speeds passing a location in a given time interval -
  • Bluetooth and Wi-Fi offer new options for travel time measurements
    November 20, 2013
    New trials show Bluetooth and Wi-Fi signals can be reliably used for measuring travel times and at a lower cost than an ANPR system, but which is the better proposition depends on many factors. Measuring travel times has traditionally relied automatic number plate (or licence plate) recognition (ANPR/ALPR) cameras capturing the progress of vehicles travelling along a pre-defined route. Such systems also have the benefit of being able to count passing traffic and have become a vital tool in dealing with c
  • Jenoptik zooms in on smarter mobility
    March 30, 2022
    As visitors to Jenoptik’s stand will see, the company provides innovative and sustainable smart mobility solutions, including technology and services for road safety, public security and road user charging. They can experience the company’s brand new video-based camera family covering a wide range of applications in road safety, civil security and commercial use.
  • Teledyne Flir brings Middle East into vision
    July 10, 2023
    As urban sprawl creeps across the Middle East and Africa, congested roads aren’t far behind. Hesham Enan of Teledyne Flir explains to Adam Hill how traffic technology is helping authorities to cope