Edge Detection of an Image Based on Extended Difference of Gaussian
Hameda Abd El-Fattah El-Sennary,
Mohamed Eid Hussien,
Abd El-Mgeid Amin Ali
Issue:
Volume 2, Issue 3, September 2019
Pages:
35-47
Received:
24 November 2019
Accepted:
9 December 2019
Published:
20 December 2019
Abstract: Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction. It's also the most important parts of image processing, especially in determining the image quality. There are many different techniques to evaluate the quality of the image. The most commonly used technique is pixel based difference measures which include peak signal to noise ratio (PSNR), signal to noise ratio (SNR), mean square error (MSE), similarity structure index mean (SSIM) and normalized absolute error (NAE).... etc. This paper study and detect the edges using extended difference of Gaussian filter applied on many of different images with different sizes, then measure the quality images using the PSNR, MSE, NAE and the time in seconds.
Abstract: Edge detection includes a variety of mathematical methods that aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The points at which image brightness changes sharply are typically organized into a set of curved line segments termed edges. The same problem of finding di...
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