written 2.1 years ago by |
Solution:
The first technique:
The first technique is color segmentation which identifies different color percentages present in the windshield/window area of the extracted image.
It is also beneficial to identify approximately which color tint is applied on the screen on the basis of the color percentage of different channels. In the present technique, the three channels of extracted area are separated out (i.e., RGB channel).
In the separated channel, a specific point is defined for finding the intensity level in the image. For better accuracy, two or more points are identified within the window region and the average intensity of the pixels is used. Then, this intensity value is represented by their intensity percentage.
According to the database available for VTL percentage for different environmental conditions, the approximate tinting level is determined.
The second technique:
The second technique used is known as contour detection which improves the tint detection of the windscreen/window of the vehicle.
Contours can be explained simply as a curve joining all the continuous points (along the boundary), having the same color or intensity. In this technique, first, we find the edges of the image by using the relevant edge detection technique.
After edge detection, the image becomes a function of two variables which are curves joining all continuous points, and these curves are called contours. These contours are in different numbers depending on the reflection of light through windshield/window glass.
The number of contours is counted in the given image.
From the available database (calculated manually) of contours for various intensity levels, the threshold (here is the number of contours) is defined and used for determining the presence or absence of tint.
If the number of contours is below the specified threshold limit, then the tested windshield/window tinting is not allowed according to the norms, and the process will switch to the next module, namely the number plate detection