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Vol.12, No.1, February 2023. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Comparative Analysis of Image on Several Edge Detection Techniques
Adi Budi Prasetyo, Rizki Wahyudi, Imam Tahyudin, Selvia Ferdiana Kusuma, Luzi Dwi Oktaviana, Azhari Shouni Barkah, Budi Artono
© 2023 Rizki Wahyudi, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 12, Issue 1, Pages 111-117, ISSN 2217-8309, DOI: 10.18421/TEM121-15, February 2023.
Received: 23 September 2022. Revised: 14 December 2022.
Abstract:
Edge detection of an image is needed to obtain information related to the size and shape of an image. There are numerous methods for detecting edges, including the Prewitt, Laplace, and Kirsch operators. Each edge detection method has different performance and results. Therefore, this study aims to analyze the performance comparison of the Prewitt, Laplace, and Kirsch operators. The analysis process is carried out using MSE, PSNR and Image Contrast values. Based on the experiments that have been carried out, the best edge detection is produced by the Prewitt operator. The average MSE and PSNR values obtained were 4.63 and 41.79 dB. The Laplace operator is good in the contrast value of 17.77. However, the contrast value only serves as a supporting parameter to clarify the differences in the results of each edge detection operator. So it can be concluded that the Prewitt edge detection method is the best method among the other two methods.
Keywords –Edge Detection, Kirsch, Laplace, MSE, PSNR, Prewitt. |
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