Sobel-Canny Fusion for Effective Edge Detection in Gaussian Denoised Digital Images

Sahana R, Sahana R, Manjula Gururaj Rao, Ganesh Aithal

2025

Abstract

Information is essential in the digital age. These data may take the shape of pictures or statistics. Getting high-quality photos is crucial when working with image data. Unwanted information in an image is referred to as noise, and it presents a major difficulty for image analysis. Depending on the image format, many types of noise may exist. Image noise removal is a difficult process. The suggested effort focusses on removing noise from colored images, especially from video frames. To improve the quality of the frames by lowering noise, the model uses Non-Local Means Denoising, Gaussian Filter, and Bilateral Filter approaches. Time performance and PSNR (peak signal-to-noise ratio) measurements are used to assess how effective the techniques are. The final photos had substantially higher PSNR values. One important component of digital image/video processing is edge detection. Edge detection is essential for applications that required to extract features or object information from a picture. Although there are several different edge detection operators are available today, improving the performance of current system remains a difficulty In this study, the Sobel and Canny edge detectors are combined in a hybrid technique.

Paper Citation

in Harvard Style

R S., Gururaj Rao M. and Aithal G. (2025). Sobel-Canny Fusion for Effective Edge Detection in Gaussian Denoised Digital Images. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 41-48. DOI: 10.5220/0013608400004664

in Bibtex Style

@conference{incoft25,
author={Sahana R and Manjula Gururaj Rao and Ganesh Aithal},
title={Sobel-Canny Fusion for Effective Edge Detection in Gaussian Denoised Digital Images},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={41-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013608400004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Sobel-Canny Fusion for Effective Edge Detection in Gaussian Denoised Digital Images
SN - 978-989-758-763-4
AU - R S.
AU - Gururaj Rao M.
AU - Aithal G.
PY - 2025
SP - 41
EP - 48
DO - 10.5220/0013608400004664
PB - SciTePress