A combination of better cameras and algorithms may help the industry overcome these challenges in the coming years.
While ALPR solutions are definitely attracting more customers, certain challenges continue to make its implementation difficult. From a technology perspective, these challenges mostly stem from the accuracy of the algorithm or their inability to work efficiently with certain cameras. But challenges are not limited to technology alone.
The environment often becomes the biggest issue that limits the capabilities of an ALPR system. Low light, rain, and similar other elements lower the quality of the image captured and the efficiency of the ALPR software.
But the challenges don’t end there. Despite the fast-paced development of sophisticated algorithms, we continue to see several issues plaguing ALPR even in 2022. Asmag.com recently spoke to industry experts to understand the significant challenges in this sector and how to overcome them.
Challenge 1: The nature of the crime
Larry Legere, Commercial Director- AutoVu at Genetec, pointed out that while crime can happen anytime, the company’s survey shows that 65 percent of violent criminal acts occur at night. This itself makes the conditions difficult for security devices. Genetec, which offers mobile and fixed LPR camera solutions for parking and investigation applications, including law enforcement, has seen significant growth in this segment over the last 12 months and expects this trend to continue.
“For many police officers, investigators, and public safety agents, this isn’t surprising,” Legere pointed out. “Not only does darkness offer criminals greater anonymity, but there are fewer witnesses around to catch them in the act. Freed up roadways also help them quickly flee crime scenes and get out of sight before first responders arrive. The challenge is that the very things that help criminals get away — lack of witnesses and information — also make it harder for investigators to solve cases.”
In addition to the challenges created by low lighting conditions, customers also need to find ALPR solutions that can recognize a wide variety of license plates and deal with the sometimes-complex infrastructure requirements necessary to power the cameras.
Challenge 2: Managing with cost-efficiency
Ensuring that the ALPR solution is cost-efficient is an important factor for businesses. This becomes even more relevant when we consider the costs of maintaining and even scaling up systems. According to Dean Drako, CEO of Eagle Eye Networks, expense, accuracy, and maintenance are the three major challenges for customers who want to implement ALPR.
“Fortunately, Eagle Eye ALPR works with regular cameras, which means that almost any standard security camera can be turned into an ALPR camera,” Drako said. “The customer does not need to purchase specialty cameras or extra onsite hardware. In terms of accuracy, Eagle Eye ALPR uses artificial intelligence (AI) that has been trained using more than one million data samples, resulting in very high accuracy.”
Drako added that his company’s solution enables accurate license plate reading even in poor weather, when the plates are dirty, with difficult camera angles, and when the license plates are non-standard (stacked characters, for example) as they are around the world.
“It’s AI-powered and ‘learns’ over time, so plate reading gets even more accurate over time,” Drako said. “Finally, Eagle Eye ALPR does not require expensive onsite maintenance, as all updates and new features are continuously delivered via the cloud.”
Conclusion
Obviously, the best solutions for concerns like low light are still based on better algorithms and technology. Legere, for instance, pointed out that the new generation of vehicle-centric investigation systems, such as Genetec AutoVu Cloudrunner, is designed to help law enforcement and public safety agencies leverage purpose-built ALPR to gather better night-time leads and solve more crimes.
Camera technology has also improved over the years, with many companies offering color footage even at night. A combination of better cameras and algorithms may help the industry overcome these challenges in the coming years.