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.

Details

Title
Comparative Analysis of Image on Several Edge Detection Techniques
Author
Adi Budi Prasetyo; Rizki Wahyudi; Imam Tahyudin; Kusuma, Selvia Ferdiana; Luzi Dwi Oktaviana; Azhari, Shouni Barkah; Artono, Budi
Pages
111-117
Publication year
2023
Publication date
Feb 2023
Publisher
UIKTEN - Association for Information Communication Technology Education and Science
ISSN
22178309
e-ISSN
22178333
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3140477511
Copyright
© 2023. This work is published under https://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.