Edge Detection Model Performance Using Canny, Prewitt and Sobel in Face Detection

Authors

  • I Wayan Rangga Pinastawa Computer Science Faculty, Informatics, University Pembangunan Nasional Veteran Jakarta, Jakarta, Indonesia
  • Musthofa Galih Pradana Computer Science Faculty, Informatics, University Pembangunan Nasional Veteran Jakarta, Jakarta, Indonesia
  • Khoironi Informatics Department, Surabaya State Polytechnic, Surabaya, Indonesia

DOI:

10.33395/sinkron.v8i2.13497

Keywords:

Edge Detection, Canny, Prewitt, Sobel, Image Processing

Abstract

Detection of objects in the form of objects, humans and other objects at this time has been widely applied in many aspects of life. The help of this technology can facilitate human work, one of which is facial detection to get information about a person's identity. Face identification and detection is closely related to Data Mining science with Image Processing sub-science. This facial detection and recognition can use several technical approaches, one of which is to use edge detection. Edge detection is one of the basic operations of image processing. In the image classification process, edge detection is required before image segmentation processing. There are several methods that can be used to perform edge detection such as Canny, Prewitt and Sobel. These three methods are methods that have accurate and good detection results, with the advantages of each method having its own added value. From the results of previous studies that stated these three methods have good results, it became interesting to conduct a comparative study of these three methods in detecting edges in facial images. Edge detection applied to this study identifies facial images, and will get similarities with the original image from the result analysis process, and is reinforced by measurement results using the Mean Square Error error degree. The final result of this study states that this study the most optimal Mean Square Error measurement results obtained the final results in the Canny method of 10, the Prewitt method of 41 and Sobel of 29. These results show that the value of the Canny method has the smallest Mean Square Error value, which indicates that the Canny method on facial image edge detection has the most optimal results.

GS Cited Analysis

Downloads

Download data is not yet available.

References

Asmara, R. A. (2018). Pengolahan Citra Digital. Polinema.

Asumu, G., Nchama, M., Daniel, L., Alfonso, L., & Cosme, A. P. (2020). Natural Images Edge Detection using Prewitt Fractional Differential Algorithm via Caputo and Caputo-Fabrizio Definitions. Global Journal of Pure and Applied Mathematics, 16(6), 789–809.

Chyad, H. S., Mustafa, R. A., & Mohamed, Z. Y. (2021). Edge Detection for Face Image Using Multiple Filters. International Journal of Engineering Research and Advanced Technology, 07(08), 28–41. https://doi.org/10.31695/ijerat.2021.3736

Khairudin, M., Mahaputra, R., Hakim, M. L., Widowati, A., Rahmatullah, B., & Faudzi, A. A. M. (2023). Choosing the Quality of Two Dimension Objects by Comparing Edge Detection Methods and Error Analysis. IAENG International Journal of Computer Science, 50(3).

Kovalevsky, V. (2019). Modern Algorithms for Image Processing. In Modern Algorithms for Image Processing. https://doi.org/10.1007/978-1-4842-4237-7

Manapa, R., Pinontoan, B., Titaley, J., Studi, P., Informasi, S., Matematika, J., & Ratulangi, U. S. (2022). Filter Citra Sketsa Wajah Menggunakan Deteksi Tepian Prewitt. Seminar Nasional Sains Dan Terapan, April, 110-115 (6 Pages). https://ejournal.unsrat.ac.id/v3/index.php/sinta6/article/view/41876/37132

Moser, G., & Zerubia, J. (2018). Mathematical Models for Remote Sensing Image Processing. In Springer. http://link.springer.com/10.1007/978-3-319-66330-2

Musthofa Galih Pradana, H. K. (2023). ANALISIS PERFORMA ALGORITMA CONVOLUTIONAL NEURAL NETWORKS MENGGUNAKAN ARSITEKTUR LENET DAN VGG16. Indonesian Journal of Business Intelligence (IJUBI), 6(2), 54–60.

Novia Wulan Dari. (2022). Identifikasi Deteksi Tepi Pada Pola Wajah Menerapkan Metode Sobel,Roberts dan Prewitt. Bulletin of Information Technology (BIT), 3(2), 85-91 (7 Pages). https://journal.fkpt.org/index.php/BIT/article/view/271/170

Pradana, M. G., Khoirunnisa, H., & Pinastawa, I. W. R. (2023). Evaluation of Convolutional Neural Network Model Architecture Performance. 628–632. https://doi.org/10.1109/icimcis60089.2023.10349075

Putra, I. K. G. D., Witarsyah, D., Saputra, M., & Jhonarendra, P. (2021). Palmprint Recognition Based on Edge Detection Features and Convolutional Neural Network. International Journal on Advanced Science, Engineering and Information Technology, 11(1), 380–387. https://doi.org/10.18517/ijaseit.11.1.11664

Saputro, P. H., Wijaya, D. P., Pradana, M. G., Tyas, D. L., & Zalmi, W. F. (2022). Comparison ADAM-optimizer and SGDM for Classification Images of Rice Leaf Disease. Proceedings - 4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022, 348–353. https://doi.org/10.1109/ICIMCIS56303.2022.10017644

Sejati, R. P. H., & Mardhiyyah, R. (2021). Deteksi Wajah Berbasis Facial Landmark Menggunakan OpenCV Dan Dlib. Jurnal Teknologi Informasi, 5(2), 144–148. https://doi.org/10.36294/jurti.v5i2.2220

Singh, H. (2018). Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python. In Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition using Python. https://doi.org/10.1007/978-1-4842-4149-3

Sundararajan, D. (2017). Digital Image Processing. In Springer. https://doi.org/10.1016/B978-012170960-0/50064-5

Toni Wijanarko Adi Putra, Eko Siswanto, D. (2021). PENGENALAN WAJAH DENGAN GLCM DAN PNN MENGGUNAKAN PENDEKATAN DETEKSI TEPI CANNY. Seminar Nasional Teknologi Dan Multidisiplin Ilmu, 14, 40–49.

Ummah, I., & Yannuansa, N. (2020). Analisis Pendeteksian Tepi Objek Pada Pengolahan Citra. Seminar Nasional SAINSTEKNOPAK Ke, 4, 118–122.

Vivian Siahaan, R. H. S. (2018). Pengantar Pengolahan Citra Digital. BALIGE PUBLISHING.

Wanto, A., Rizki, S. D., Andini, S., Surmayanti, S., Ginantra, N. L. W. S. R., & Aspan, H. (2021). Combination of Sobel+Prewitt Edge Detection Method with Roberts+Canny on Passion Flower Image Identification. Journal of Physics: Conference Series, 1933(1). https://doi.org/10.1088/1742-6596/1933/1/012037

Yasir, M., Hossain, S., Nazir, S., Khan, S., Sakaouth Hossain, M., Thapa, R., Hossain, S., Nazir, S., & Khan, R. T. (2022). Object Identification Using Manipulated Edge Detection Techniques. Science Development, 3(1), 1–6. https://doi.org/10.11648/j.scidev.20220301.11

Downloads


Crossmark Updates

How to Cite

Pinastawa, I. W. R. ., Pradana, M. G., & Khoironi, K. (2024). Edge Detection Model Performance Using Canny, Prewitt and Sobel in Face Detection. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 8(2), 623-631. https://doi.org/10.33395/sinkron.v8i2.13497