Introducing Verkada License Plate Recognition

Today, we’re excited to announce the launch of Verkada’s License Plate Recognition solution. With Verkada LPR, we’re applying the powerful capabilities of our industry-leading computer vision technology to deliver highly accurate license plate detection and recognition.

Verkada LPR incorporates a dual-camera approach for delivering accurate plate readings while showing a complete view of vehicle activity. All events are displayed in a new LPR page in Command, making it easy to see every license plate capture alongside a video clip of the event.

Unlike competitors' expensive, purpose-built solutions, Verkada LPR is bundled into your Verkada Command License and is supported by Verkada’s Bullet series cameras. Simply toggle your Bullet camera into LPR mode and pair with a context camera to begin capturing highly accurate LPR results.

Complete Vehicle Coverage

Most LPR solutions rely on a single camera to both analyze license plates and monitor the scene. This approach limits LPR accuracy and scene coverage.

We’ve taken a dual-camera approach to solve for the distinct needs of LPR and general video security. In Verkada’s LPR solution, one camera is designated as the LPR Camera while the other is set as a Context Camera.

The LPR Camera leverages the powerful zoom capabilities of Verkada’s Telephoto Bullet Series to deliver high-resolution, close-up license plate captures. Each LPR Camera operates in a dedicated LPR Mode, which records all footage using the Bullet Series’ long-range IR sensors.

In real-time, the LPR Camera uses a powerful onboard processor to analyze each individual plate, surfacing the string of characters for easy monitoring and search.

Each LPR Camera is paired with a Context Camera to provide whole scene coverage. While the LPR Camera is focused on capturing the perfect plate image, the Context Camera records the broader scene, including the vehicle, driver, and other pertinent details.

Investigations Made Easy

From Command, Verkada’s software integrates both the LPR Camera and Context Camera to provide users with comprehensive visibility of each vehicle event.

For each plate capture event, users can see a video clip of the vehicle from their Context Camera, side-by-side with a snapshot of the license plate and searchable text capture of that plate.

Users can drill into the historical footage, as well as digitally zoom, capture a screenshot or archive the footage for future investigations. For even greater context, users can pair additional Context Cameras to see events from multiple angles or hone in on particular scene details.

From the LPR page, users can search all detected plates for partial or complete license plate matches and see time-stamped events for all vehicle sightings. Users can also filter results based on certain cameras or date ranges. For any given search, the complete list of license plate results can be exported to a CSV file for offline analysis.

Additionally, organizations can leverage Verkada's set of webhook APIs to integrate license plate events with third-party tools already in-use, such as for tracking plates detected on site.

Getting Started

We’ve made it simple to set up your organization’s LPR Cameras.

Once you’ve designated a camera for LPR (including installing the camera at the proper height and angle), simply follow the steps in Command for optimizing your camera. These steps include:

• Adjusting the camera’s zoom and focus

• Highlighting the license plate area of interest

• Adding your Context Camera

After following these steps, your camera should begin to detect license plates, which will be shown in the LPR tab of Command.

Verkada LPR has been designed for parking lots, garages, car washes, and other sites where vehicles are traveling at less than 20 miles per hour and cameras can be mounted less than 40 feet from the license plate.

Verkada’s LPR Solution is available now. If you’re interested in learning more about how Verkada can help your organization detect vehicles, please contact [email protected].