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Top 5 ANPR license plate recognition companies: 2022 reader survey

Top 5 ANPR license plate recognition companies: 2022 reader survey conducted a reader survey earlier this year to better understand the ANPR/ALPR market landscape and determine what users prioritize in terms of license plate recognition features. A total of 142 respondents (security industry channel players) completed the ANPR portion of the poll.
An automatic number/license plate recognition (ANPR or ALPR) system uses smart cameras and video analytics to recognize license plates without human intervention and compare them with an existing database for authorization and access control. Organizations are deploying automated LPR systems for site vehicle management and security, traffic management, and to improve overall tenant user experience. conducted a reader survey earlier this year to better understand the ANPR/ALPR market landscape and determine what users prioritize in terms of license plate recognition features. A total of 142 respondents (security industry channel players) completed the ANPR portion of the poll.
The survey posed three open-ended questions:
  • Which 3-5 ANPR/ALPR camera brands come first to mind and would recommend to your peers?
  • Which features made each of these license plate recognition camera brands your top choice?
  • If you can give manufacturers a wish list, which services/features are lacking or need improvement?

Survey methodology and demographics >

Question 1 -The top 5 companies for ANPR camera solutions

According to the survey, the top 5 leading license plate recognition companies are Hikvision Digital Technology (44%), Axis Communications (31%), Dahua Technology (25 percent), Hanwha Techwin (15%) and Avigilon (14%). Other ANPR brands that got a significant number of votes are Bosch, Adaptive Recognition (formerly known as ARH), Milesight, Tattile, Vivotek, and Uniview Technologies.
2022 reader survey: Top 5 ANPR brands
Hikvision Digital Technology 44%
Axis Communications 31%
Dahua Technology 25%
Hanwha Techwin 15%
Avigilon 14%

Since our respondent pool consisted of security industry professionals, it's of no surprise that majority of the top license plate recognition manufacturers belong to those with ANPR solutions that compliment their security and surveillance portfolios. Two names might be a bit unfamiliar to some of our readers though. Adaptive Recognition (previously ARH) is an AI-based image processing technology provider for traffic, security and identity industries with its flagship Carmen ANPR software. Another interesting name in the LPR ranking is Tattile, an Italian manufacturer of license plate reader cameras and application software for ITS, mobility and smart cities that was acquired by big smart/machine vision firm TKH group in 2018. 
Top 5 license plate recognition brands quicklook:

Question 2 – Top ANPR product features the industry is looking for

Top 5 priorities for survey respondents: Features > Quality > Accuracy > Price > Brand Name
Key product features for respondents include image quality, large database, integration, and local/global application.

ANPR cameras commonly are equipped with deep learning algorithms and GPU processors, using optical character recognition (OCR) to “read” number plates. However, this requires the capture of sharp, clear images to “read” from. Therefore, it is not surprising that most respondents cited image, lighting and video compression technologies as top feature considerations.
  • “Good illuminator and lens.”
  • "Optical zoom and light sensitivity for clear capture of images for traffic and accident monitoring."
  • "Advanced infrared technology and H.265+ compression technology."
Another important aspect raised in the survey is their integration capabilities with access control and parking management applications.
  • “The presence of a vehicle can be detected with no need for external sensors, and the device can automatically open the barriers at entrances and exits.”
  • “Easy configuration of parameters, easy software linkage, applications in roads and as access control.”   
Also worth mentioning are local/global application requirements. Some respondents pointed out that they chose certain license recognition camera brands based on compatibility with number plate formats in their own/other countries.
  • "Approved by local authorities for city connectivity here in Dubai."
  • "Milestone is able to support several countries' license plate."
  • "Hikvision supports countries and regions of Mid-East, Africa, Asia-Pacific, America, Europe, Russian-speaking countries.
  • "Support for Thai license plates and low cost.

Question 3 – Top requested features for ANPR manufacturers

Readers are asking for improvements in Features > Integration > Price > Accuracy > Post-sales service

Image quality being a priority, a significant number of requests were to improve camera zoom distance for reliable license plate reading.
  • "Focus even when the camera is installed from the 20 meters far from the object."
  • "Improve on the zoom function, make it smarter and faster."
  • "In low-light, the camera should be able to capture an image while still retaining image quality."
  • "Enhance image process(ing) for unrecognized license plates."
Regarding working under challenging light and weather conditions, one respondent had a sound recommendation for ANPR manufacturers:
  • "The key features are the Illumination and the F-stop of the camera. The best tip that I would give manufacturers is to have a schedule for configuration that is not the same as the parameters for the day and the night. For example, change parameters like shutter speed, or even change to B&W to get a better performance in the night."
The theme of integration from the above list also continued here as well.
  • "Better interoperability and integration with various brands. Or even add your own AI layers."
  • "Better visitor module and parking management."
  • "The function of independent work for simpler demands (e.g., opening and closing the sliding gate when the permitted license plate is detected)."
  • "Every country has rules, such as 1. ODOL Overload, Over Dimension. 2. Motorcycle: Helmet violation, Motorcycle driven by more than two passengers, integration with 3rd party ANPR software of the domestic market, get all kind of national certificates."
One thing to note here is the call for “lower prices” here holds true per unit as well as for more cost-competitive subscription and licensing fees.
  • "Wider selection of high-performance mini-cameras for hidden installations. Move away from high licensing fees, especially when the cameras and software are of the same brand."
 More analytic features and stronger AI algorithms for better image and video processing for more intelligence and applications.
  • “Besides ISS, we wish Genetec and others will add features such as make, model recognition."
  • "AI to co-relate events and easy way to push LPR data as Wiegand data to access control as a reader
  • "Built-in alarm systems for intrusion, noise, overcrowding deterrence."
Not as high on the wish list but perhaps warranting more discussion are two requests.

One, a number of respondents are pushing for “more powerful edge analytics,” “on-board analytics,” and recommendations “…that the analysis of the plate recognition system is inside the standard analysis, and it is installed in the camera's chipset."
The other request on the feature wishlist was about camera wiring and connection:
  • "Long-distance PoE that can reach the needs of power of the cameras.”
  • "Use PoE and have connections in housing to eliminate the need for connection boxes outdoor."


License plate recognition is popular, but there is still a lot that solution providers can do to make them better. The top five companies are from different parts of the world, indicating respondents are not limited to any brands from any particular region when it comes to ANPR.
As the technology progresses, the solutions may be able to address some of the major concerns that customers have, such as more accurate results in tough conditions, support for different plate standards, and integration of more AI.  
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