We developed a driver assistant which is a software running on mobile phone devices and increasing safety during a car drive. The software monitors a road in front of a car in a real time. The software running on a mobile phone placed on the front shield of a car activates a color and sound alarm whenever the car leaves the road. Additionally, two further functionalities are added, in particular, the sequence of images is recorded in a loop (black-box) and accurate GPS speedometer.
The main core of the software is a line detection algorithm which detects lines painted on the road. The motivation was the standard Hough Transform for a line detection. The essential point of the Hough Transform is a transformation of the image to the dual space, e. g., of line orthogonal distance from the origin and the angle of the line slope. However, this approach demonstrated low robustness w.r.t. rather frequent disturbances from the \optimal line". For instance, a shadow shed on a white line caused it was not detected or moderate curve was not detected either. Indeed, in the first case, the algorithm did not see it white enough, in the second case, it was not found straight.
Therefore, we proposed to replace each image pixel intensity with a fuzzy number and thus, to obtain an image represented by a fuzzy function. This idea was motivated by the intended increase of the robustness. For the sake of computational costs, triangular fuzzy numbers were chosen to be applied in the fuzzication process. Then, the Hough Transform was modifed in order to work over the proposed structure. The dierence consists in the computation of the approximate gradient magnitude instead of the computation of gradient magnitude using standard operators. The intensity we search for (color of the searched line) is placed into an argument of fuzzy number of the fuzzied image in its each point and thus, its membership degree to the given fuzzy number is evaluated. This membership degree is taken into account only if exceeding a given threshold. Consequently, the whole task in the dual space is again performed using the membership degrees.
The proposed approach was experimentally verifed confirming its advantage in terms of speed and robustness (reliability). Using the proposed algorithm for a line detection we built an Android mobile phone application for the analysis and tracking of the road. Its processing speed is approx 15FPS. Furthermore, some other se were also implemented, e.g., the above mentioned frames in-loop recording (black-box) and the GPS speedometer, or a sound and visual alarm for the signicant warning in the case of departing a road.