Calculating Nominal Resolution during Content Triage

In the image / video analysis workflow, the Content Triage step examines the file's contextual information from the standpoint of "can I answer the question with this file?"

The Content Triage step necessarily involves Frame Analysis. Part of Frame Analysis considers the calculation of the Nominal Resolution of the target area - face, shirt, tattoo, license plate, and etc. In this post, we'll consider license plates (aka number plates or registration plates) as our target.

Dimensionalinfo.com notes that in the US, standard license plate dimensions are six inches by twelve inches or approximately one hundred and fifty-two millimeters by three hundred and five millimeters.

Image source

In the United Kingdom for instance, the standard dimensions for registration plates are five hundred and twenty millimeters by one hundred and eleven millimeters for the front plates while the rear plates measure can be of the same dimensions or two hundred and eighty-five millimeters by two hundred and three millimeters.

Australia on the other hand, has standard dimensions of three hundred and seventy-two millimeters by one hundred and thirty-five millimeters or approximately fourteen and one-half inches by five inches.

The SWGDE Digital & Multimedia Evidence Glossary, Version: 3.0 (June 23, 2016), defines Nominal Resolution as "the numerical value of pixels per inch as opposed to the achievable resolution of the imaging device."  "In the case of digital cameras, this refers to the number of pixels of the camera sensor divided by the corresponding vertical and horizontal dimension of the area photographed."

Let's put this all together with an example from Australia. The question / request is: can we resolve the registration plate's characters on the white care, upper center left of the image shown below.

Ordinarily, you might be tempted to just say not, it's not possible. It's too small. Which of those few pixels do you want me to Photoshop into a registration plate? In this case, we'll attempt to quantify the value of the Nominal Resolution of the target area.

If the typical Australian registration plate is 372mm wide, and the target area is 8px wide, then the Nominal Resolution is ~46.5mm per pixel - meaning each pixel covers a width on target of ~46.5mm (about 1.8 inches). How many pixels wide are needed to resolve characters in a registration plate? My tests have shown results in a few as 5-6 columns of pixels wide can work at distances to target of under 15' for typical CCTV systems. Given that a pixel is generally thought of as the smallest single component of a digital image, you'll need more than a few to resolve small details in an image or video in order to answer questions of identification.

But, but, but ... the video system's specs note that the camera is HD and the recording is 1080p. The system's owner spent a lot of money on the tech. So what?!

Nominal Resolution deals with the target area, not the system's capabilities. The key is distance to target. The farther away from the camera, the lower the Nominal Resolution. The lower the Nominal Resolution, the lower the chance of successfully answering identification questions.

Thus, when responding to requests for service, it's a good idea to calculate the Nominal Resolution of the target area in order to quantify the pixel density of the region, adding the results to your conclusion. A statement such as, "unable to fulfill the request for information, re registration plate details, due to insufficient nominal resolution (~46.5mm per pixel)," is a lot more informative than "sorry, can't do it." If the available data supports no conclusion, adding the quantitative reasons for your conclusion will go a long way to supporting your determination.

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