Deteksi Zebra Cross Pada Citra Digital Dengan Menggunakan Metode Hough Transform - Fitria Indriani; Fitri Utaminingrum; Yuita Arum Sari (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
The high number of accidents that injure pedestrians while crossing is caused by motorists who are less cautious. Accidents of course undesirable can be prevented and minimized the culture of orderly traffic one by using facilities such as zebra cross. In this research, we propose the process of zebra cross detection on digital image using Hough Transform method, in order to be implemented in smart vehicle navigation system in identifying zebra cross in order to increase equality of both riders and zebra cross users. The zebra cross detection process starts from pre-processing, which consists of grayscaling process, mean filtering, dilation, and histogram equalization, for our edge detection using the next stage canny method is the image inversion which aims to change the pixels of white to black, and vice versa. Then for line detection on zebra cross using hough transform method. Based on the test, the highest accuracy value when the 100 threshold value on the first morning condition test data is 95.2%. The result of testing the variation of the structure element obtained the maximum results with the use of rectangle has the highest accuracy value of 95.2% compared with the use of other structure element form. In the result of testing edge detection sobel has the highest accuracy value of 92.8%.