Best Image for Automatic License Plate Recognition – ALPR – part 2 Contrast

Now that you have done what is possible to get a sharp image for your OCR algorithm for automatic license plate recognition, another image quality parameter that is critical is contrast.

Contrast is the difference in brightness between the light and dark areas.  Much finer details can be detected if the difference between the light and dark areas is more pronounced.

Figure 1.  Example image with poor contrast

Here are some suggestions on ways to improve contrast that are specific to the needs of ALPR:

Exploiting Higher Frame Rates of a Camera

Cameras with higher frame rates allow for multiple images to be taken of the same object with different exposure times. This way multiple images under different conditions are available and the best one can be selected.  There are now CCD cameras available with 2MP HD resolution and speeds of more than 60 frames/second. For CMOS cameras [see blog comparing CCD and CMOS for traffic applications], the speeds can be more than 5 times higher.

Using Cameras with a High Dynamic Range

Image sensors with high dynamic range can distinguish the foreground (the license plate characters) better from the background. For license plates in certain regions of the world, this is particularly challenging.  If implemented properly, camera manufacturers ensure the full linear dynamic range of the sensor is available or can even add functionality to increase the dynamic range.

Lighting

Poor reflection of light on the license plate can limit the contrast.  Different license plates have different reflection coefficients.  As with optimizing sharpness, for optimal results, the wavelength of the IR lighting must be matched with the license plate to be measured.

Snow, rain, and fog also reflect the IR LED.  Again, special attention to the IR wavelengths to use will enhance the contrast of the image.

So multiple images from a fast camera that also has high dynamic range combined with optimized IR lighting will produce good contrast results in the image. This improves the efficiency of the OCR algorithm and giving the system integrator a better chance to win the tender contracts. In the end the return on investment will be greater and ultimately road safety is improved.

Next we will discuss how to minimize artifacts such as blooming and smear.