Unlike what is shown on TV, you cannot zoom into a blurry image and expect to get more details. An image with acceptable sharpness and contrast must be acquired from the start using an appropriate system. This means combining the right image sensor, camera, optics, and lighting in a reliable way.

So, what defines good image quality for automatic license plate recognition (ALPR)?

The first step is to ensure reliable triggering so that the license plate appears in the proper location of the image—an especially tricky challenge in multi-lane systems. After accurate positioning, a high-quality image can be characterized by:

  • Good sharpness
  • Sufficient contrast
  • Freedom from artifacts
  • Sometimes accurate color reproduction

These qualitative attributes are easier to understand with visuals:

Figure 1: Artifacts caused by insufficient lighting control
Figure 2: Insufficient sharpness due to motion blur
Figure 3: Insufficient contrast because of limited dynamic range

For more background on ALPR acquisition algorithms and technology, visit: http://www.platerecognition.info/1102.htm

The sources of these image quality issues can vary. Below is a table outlining common limitations and how to address them:

Image Quality Parameter Corresponding Source of Limitations Image System Parameters to Control
Sharpness Limited depth of field, motion blur, variable lighting Lens F-value, image sensor sensitivity, iris control
Contrast Fewer images captured, reflections on the plate or road Image sensor/frame rate, dynamic range
Artifacts Ghosting, bright spots/streaks from glare/reflections Filter/lens/alignment, channel matching, camera blooming/smear
Color Inaccurate color reproduction Automatic white balance, accurate color calculations

Proper alignment of the entire optical path is critical for image quality—especially at high speeds. The higher the input image quality, the better the starting point for ALPR algorithms, resulting in improved accuracy.

For detailed guidance on optimizing sharpness and contrast while minimizing artifacts, stay tuned to our upcoming blogs:

  • Opportunities and challenges of machine vision advancements for intelligent transportation systems (ITS)
  • Camera requirements for different automatic license plate recognition (ALPR/ANPR) applications
  • Learn more about accurate color reproduction here.

Last Updated: 2025-09-04 18:56:28