With the technology today, detection of pedestrian was introduced to decrease the accidents in the roads. It was implemented on the traffic lights and cars. In this paper, integration of face detection and pedestrian takes place on the device called Raspberry Pi. OpenCV was used for the detections and programmed in Python. The webcam was used to capture images in real-time. The images was processed at the microprocessor. When pedestrians were detected, the microprocessor played the recorded voice and outputs it to the connecting speaker to notify those pedestrians or the pedestrian to wait before crossing until such time. The microprocessor sends a signal to the Gizduino to process the time of the red light’s on state. The microcontroller was programmed with the traffic signals. When it receives a signal from the microprocessor, it added an extra seconds to the red light’s on state. Afterwards, when it returned, it changed back to its original on state. The methods used for analyzing the data obtained were the Classification method and the Chi-square statistical test analysis. After testing, gathering data and computing each classification with the use of chi-square formula, the result of the success rate was 87.33% that showed that face and pedestrian detection that was integrated in the system successfully worked. (Author/publisher)
Abstract