Image Edge-Segmentation Techniques : A Review

Authors(3) :-Rana Riad K. Al-Taie, Basma Jumaa Saleh, Lamees Abdalhasan Salman

Image segmentation is commonly applied technique in different domains such as automatic pattern recognition, image retrieval based content, machine vision, face detection, medical imaging, and object detection. Image segmentation involves classifying or identifying sub patterns in a given image. Many of algorithms and techniques for image segmentation have been proposed to optimize segmentation problems in a specific application area. In this work, different image segmentation techniques had been applied (threshold based, region based segmentation and edge based preserving methods. This Experiment have been done using MATLAB R2018b. Different edge detection methods such as Sobel, Prewitt, Roberts, Laplacian, Kiresh and Canny methods are performed on the benchmark image and the performance is analyzed with respect to the standard measure peak signal-to-noise ratio (PSNR), and mean square error. The results present that the Laplacian method is more effective than the other methods.

Authors and Affiliations

Rana Riad K. Al-Taie
Department of Computer Engineering/ Al-Mustansiriyah University/ Baghdad, Iraq
Basma Jumaa Saleh
Department of Computer Engineering/ Al-Mustansiriyah University/ Baghdad, Iraq
Lamees Abdalhasan Salman
Department of Computer Engineering/ Al-Mustansiriyah University/ Baghdad, Iraq

Segmentation, Edge-Preserving, Image Processing

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Publication Details

Published in : Volume 8 | Issue 5 | September-October 2021
Date of Publication : 2021-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 252-257
Manuscript Number : IJSRSET218528
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Rana Riad K. Al-Taie, Basma Jumaa Saleh, Lamees Abdalhasan Salman, " Image Edge-Segmentation Techniques : A Review, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 5, pp.252-257, September-October-2021. Available at doi : https://doi.org/10.32628/IJSRSET218528      Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET218528

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