Implementation of the Laplacian of Gaussian Algorithm in Edge Detection Image Processing of Zebra Cross Damage on Highways in the Langkat Regency Area


  • Ratih Puspadini STMIK KAPUTAMA
  • Melda Pita Uli Sitompul STMIK KAPUTAMA



Image, Zebra Cross, Laplacian of Gaussian


Walking is part of the traveler's movement and is the simplest means of transportation, but it is in a weak position and prone to conflict or accidents when they mix with other modes of transportation. To protect pedestrians, special facilities are needed, one of which is a crossing place (zebra crossing) that is able to serve according to pedestrian needs. Based on Law No. 22 of 2009 concerning Traffic Polytechnic Land Transportation Bali 46 Cross and Road Transportation, article 131 paragraph (2), it is stated that "Pedestrians are entitled to priority when crossing the road at the crosswalk". One of the important meanings for human life is the Way. Roads are used as a means of transportation that has a very useful role in efforts to develop human life. In 2018, based on statistical data, the number of motorized vehicle users in Indonesia is increasing every year to reach 146,858,759 units. The impact that occurs is that there are many Zebra Cross roads damaged with conditions that are very troubling and worrying for road users. Among the causes of zebra crossing being damaged will be traffic accidents where the vehicle does not lag obeying the path of the vehicle following the predetermined lane. So this study detects image processing  with the Laplacian of Gaussian algorithm with edge detection making it easier for the government to improve traffic signs of zebra crossing images on highways that are worthy of improvement so that accidents do not occur. The results of this study illustrate the image of being able to see damaged zebra crossings with calculations of the Laplacian of Gaussian algorithm.


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S. Aripin, L. Sarumaha, and M. N. Sinaga, “Implementasi Metode Laplacian of Gaussian Dalam Deteksi Tepi Citra Gigi Berlubang,” Semin. Nas. Teknol. Komput. Sains, pp. 393-396 (4 Pages), 2020.

L. Sukmawati and R. Sadikin, “Segmentasi Jalan Berlubang Citra Jalan Raya Menggunakan Metode Thresholding Dan K-Means,” J. Tek. Komput., vol. 9, no. 2, pp. 89–95, 2023, doi: 10.31294/jtk.v9i2.15211.

A. Z. Hasibuan, “Penerapan Edge Detection Pada Citra Digital Menggunakan Operator Laplacian Of Gaussian,” Semin. Nas. Teknol. Inf. dan Komun., no. 70, p. 3, 2013, [Online]. Available:

A. B. Sulistyo, “Zebra Cross Batik Untuk Meningkatkan Kesadaraan Perilaku,” vol. 1, no. 1, pp. 45–50, 2020.

R. Haryono, “Penerapan Metode Laplacian Of Gaussian Dalam Mendeteksi Tepi Citra Pada Penyakit Meningitis,” KLIK (Kajian Ilm. Inform. Komputer), vol. 1, no. 1, pp. 20–26, 2020, [Online]. Available:

M. Z. Andrekha and Y. Huda, “Deteksi Warna Manggis Menggunakan Pengolahan Citra dengan Opencv Python,” Voteteknika (Vocational Tek. Elektron. dan Inform., vol. 9, no. 4, p. 27, 2021, doi: 10.24036/voteteknika.v9i4.114251.

J. Jumadi, Y. Yupianti, and D. Sartika, “Pengolahan Citra Digital Untuk Identifikasi Objek Menggunakan Metode Hierarchical Agglomerative Clustering,” JST (Jurnal Sains dan Teknol., vol. 10, no. 2, pp. 148–156, 2021, doi: 10.23887/jstundiksha.v10i2.33636.

P. S. Fisika, “Aplikasi Matlab pada Teknologi Pencitraan Medis,” vol. 1, no. 1, pp. 28–34, 2019.




How to Cite

Puspadini, R., & Sitompul, M. P. U. (2024). Implementation of the Laplacian of Gaussian Algorithm in Edge Detection Image Processing of Zebra Cross Damage on Highways in the Langkat Regency Area. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 3(2), 601–605.