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  1. Home
  2. Faculty Publications
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  4. Egf: An Improved Edge Detection Model for Low-Resolution Images
 
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Egf: An Improved Edge Detection Model for Low-Resolution Images

Date Issued
2023
Author(s)
Deepak Raj, D M  
Shanmuganathan, Harinee
Geetha, A  
Keerthika, V  
DOI
https://doi.org/10.1109/INCOFT60753.2023.10425353
Abstract
Edge detection can benefit many different industries and domains, including computer vision, machine learning, image analysis, remote sensing, thermal imaging, pattern recognition, and medical imaging. The technique of determining the borders between several objects or regions in an image is known as edge detection. The edges of an object in a picture serve as the object's limits and can reveal crucial details about the object's size, shape, and position. Since low-resolution images have low pixel densities or pixel values, which muddy the images, detecting edges in them is demanding work. This paper proposes a novel edge-detection approach called EGF (Extended Gaussian Filter) for low-resolution images. EGF utilizes the basic concept of Gaussian filter to find the edges of images. The objective function of EGF is developed to reduce the noise and pixel differentiation in images. The outcomes show that the suggested strategy outperforms the conventional edge detection technique. © 2023 IEEE.
Subjects

Edge Detection

Gaussian Filter

Image Processing

Machine Learning

Pre-Processing

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