Solution:

Third technique level:

The third technique is called “Histogram analysis” and is used for visually judging whether the image is in an appropriate range of gray level.

Ideally, the digital image should use all available gray-scale ranges, from minimum to maximum.

From the histogram of the tint image (final extracted image), we can judge the presence of tinting on the windshield/window. If the histogram of the extracted image has only two peaks of gray level, then it has an undesired tinting level.

If the histogram of the extracted image shows multiple peaks in the histogram, then we can conclude that there is a desirable level of tinting. These three methods collectively can determine the tinting level of the window/windshield region.

The figure shows the flow chart of various tint level detection algorithms used in our present work.

After identifying the tinting level of the vehicle window/windshield using these three techniques, the process is switched to the number plate identification module.

If the tinting the level is more than the desired level (prescribed norms by state/country), then it switches to the number plate identification module; otherwise, the test ends for the current vehicle.

After identifying the license plate registration number of a given vehicle, the system captures the image of the vehicle for proof and saves it in a controller (or server).

The controller is interfaced with a GPS device which provides the location details of the place where the images were captured and append the system date and time.

All these parameters are sent to the server system which stores all the received data.

The vehicle registration number is extracted from the captured image and is searched in the available database, and the vehicle owner’s contact details are traced for sending evidence to issue a ticket.