Traffic control by digital imaging cameras - Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition - page 200

FIGURE 11 PNR.
Figure 12 represents the correlation between the input numbers and the templates, in the
illustrated plate. Figure 12 shows the correlation for the first element number (2) and the tem-
plates. Figure 12 shows that its maximum correlation was with templates of number (2).
FIGURE 12 Correlation of number (2).
8 General Conclusion
Based on the results and the observation of the performance of the project code, the following
conclusions can be drawn:
• MATLAB was a very helpful programe to use; it has all the required toolboxes and demos.
• The results of image processing were very good for the purpose of this project, the opera-
tions used to edit the images have done the task successfully.
• The camera specifications played an important role in the accuracy of the code, as it is bet-
ter, the accuracy will be beter.
• This project can make a good drop in the cost comparing to the other systems are being
used in the traffic controlling, as it only needs a computer, high-quality camera, and the
MATLAB license.
8.1 Problems
The problems faced in this project were mainly the low quality of the camera used since the
video contains a moving car, for that the camera lens and zoom must be at a high quality, and
it also needs a high processor computer for the MATLAB to work properly.
In the red violation, our tested zone was an intersection of three lanes so the moving cars
left no space for us to put our testing points, which implies that we need a higher position of
camera to see the empty space needed for testing points.
In the plate recognition what we faced that some of the plates have some nails on them for
some stains which make it harder to extract the numbers correctly.