In process of design video surveillance systems – our clients always tell us that they need license plate recognition by camera at their main entrance, but what they usually mean is license plate capturing. License plate camera capture is the process of recording an image of a license plate. In contrast, license plate recognition uses that image to identify and look up the license plate in a database. License plate recognition is generally intended to associate a vehicle with a person, especially by law enforcement and private security agencies.
The following discussion outlines the differences between the two applications and the key factors that determine the success of each method. Watch the short video below or continue reading.
License plate capture
Using a security camera to capture a license plate requires you to consider both the capabilities of the camera and your environment. Every environment is unique, so there is no one-size-fits-all license plate recognition camera. In particular, a megapixel license plate camera solution should be dedicated to that task due to the specialized nature of this application. The key technical elements that a video surveillance consultant uses to capture a license plate with a camera include:
- Frames per second
- image quality
- Turning on
- image stabilization
- Exhibithion time
- Angle
- Speed
Frames per second
The speed at which a camera takes pictures is usually measured in frames per second (fps). The higher the frame rate, the more likely it is that you can capture a moving car license plate. However, frame rate is inversely proportional to resolution, which means that increasing the camera’s frame rate reduces the resolution of the image. The frame rates of the cameras used to capture license plates are typically between 30 and 60 fps.
Image Quality Capture License
Pixel density primarily determines the quality or resolution of a camera’s image. Resolution is typically measured in pixels per foot (ppf) or pixels per meter (ppm). An image processing software will have a specific resolution requirement, but human readers are much more subjective. A high-resolution surveillance camera used for license plate cameras typically has a pixel density of at least 60ppf or 110ppm.
Turning on
A camera requires a longer exposure time to compensate for poor lighting, resulting in a reduced frame rate. In particular, license plate capture lighting increases the challenge of capturing license plates at night. The most common solution for surveillance camera lighting is to position the camera so that it is not looking directly at a light source, which usually means it is placed 10-15 feet above the ground. A case with a high contrast filter is another option for managing glare at night.
image stabilization
Image stabilization is a collective term for techniques that reduce blur caused by a camera taking a photo while moving relative to the subject. These techniques primarily compensate for pan and tilt, although some cameras also compensate for roll. Image stabilization is critical with long shutter speeds and when using lenses with long focal lengths, such as telephoto and zoom lenses.
Exhibithion time
A longer exposure time, or shutter speed, increases motion blur and reduces the camera’s light requirements. A camera in a high-speed location, such as on the street, will typically need a shutter speed of no more than two milliseconds. On the other hand, a camera covering a location with slow-moving vehicles, such as a gate or parking lot entrance, can have a shutter speed of up to four milliseconds.
Image angle
The license plate camera should be positioned so that its line of sight is perpendicular to the surface of the license plate below. ideal circumstances. However, conditions such as glare may require the camera’s line of sight to be at a flatter, more skewed angle to the license plate. In these cases, a longer focal length and license plate distance can minimize the effects of a skewed angle.
Capture speed of a license plate image
The speed of a vehicle has a direct effect on the challenge of capturing a license plate. A higher speed requires a higher frame rate to record an image with the vehicle in the correct position. However, a faster shutter speed will require more light.
License Plate Recognition
License plate recognition is also known by many other names, including license plate recognition (LPR) and automatic license plate recognition (ALPR) in the United States. It includes the necessary processing to extract the alphanumeric value of the license plate, based on a series of algorithms. The ALPR software will then compare this value to the license plates stored in a database. Database-based ALPR systems can be classified into stand-alone systems and systems integrated with third-party video management software.
License plate recognition algorithms
LPR systems currently use the following seven types of algorithms to identify a license plate number:
- plate location
- Orientation and size of the plate
- Standardization
- character segmentation
- Optical character recognition
- Syntactic and geometric analysis
- average
License plate location algorithms identify the license plate in a given image and isolate it from the rest of the photo. Plate size and orientation algorithms compensate for a skewed image and adjust to its size. Normalization is the process of adjusting image brightness and contrast, while character segmentation algorithms identify individual characters on the plate. Optical Character Recognition (OCR) is the conversion of printed text to encoded text. Initially it was used to encode documents, but OCR algorithms have since been specifically designed for license plate recognition.
Parsing and geometric analysis involves the use of country-specific rules to identify characters and their positions within the license plate number. It may also be necessary to average the recognized values across multiple images to increase the confidence of the identification. This algorithm is essential for license plate recognition, since the images often contain reflected light and partial obstructions.
ALPR systems of independent license plates
Standalone LPR systems perform the entire recognition process on site, in real time, and typically in a fraction of a second. This process includes capturing the license plate image and recording associated information such as lane identification and date/time. An independent LPR system may store this data on the site or transmit it to a different computer off-site for further processing.
Software Integration
An ALPR system can be integrated with third-party software that is not made by the system manufacturer or its servers. These systems will transmit images to a remote location as they are being recorded, allowing the software to further process the images. ALPR software typically runs on standard personal computers (PCs) and can be linked to databases and other applications. This arrangement typically uses a server farm containing many PCs, allowing the ALPR system to handle large workloads. The need to continuously stream images to a remote server also requires high-bandwidth streaming media.
The best camera for license plate capture and license plate recognition
The nature of license plate capture and recognition systems means that they must function correctly at all times. Choosing the right video surveillance and camera installation company can be a crucial decision, especially when looking for a license plate capture technology or recognition system. A security camera installer must select each camera for the specific application and environment due to the unique challenges of capturing and recognizing moving vehicle license plates. A security company also needs to set the shutter speed correctly, as there is often a narrow gap between a shutter speed that can make an image too dark and another that can make it too blurry. Contact the video surveillance experts at Umbrella Technologies for a free consultation on the best license plate capture camera for your needs.
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