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Type :article
Subject :TK Electrical engineering. Electronics Nuclear engineering
ISSN :2169-3536
Main Author :Haidi Ibrahim
Additional Authors :Wang, Shir Li
Title :Quality assessment methods to evaluate the performance of edge detection algorithms for digital image: a systematic literature review
Place of Production :Tanjung Malim
Publisher :Fakulti Seni, Komputeran Dan Industri Kreatif
Year of Publication :2021
Notes :IEEE Access
Corporate Name :Universiti Pendidikan Sultan Idris
HTTP Link :Click to view web link

Abstract : Universiti Pendidikan Sultan Idris
A segmentation process is usually required in order to analyze an image. One of the available segmentation approaches is by detecting the edges on the image. Up to now, there are many edge detection algorithms that researchers have proposed. Thus, the purpose of this systematic literature review is to investigate the available quality assessment methods that researchers have utilized to evaluate the performance of the edge detection algorithms. Due to the vast number of available literature in this area, we limit our search to only open-access publications. A systematic search in five publisher websites (i.e., IEEExplore, IET digital library, Wiley, MDPI, and Hindawi) and Scopus database was carried out to gather resources that are related to the edge detection algorithms. Seventy-three publications that are about developing or comparing edge detection algorithms have been chosen. From these publication samples, we have identified 17 quality assessment methods used by researchers. Among the popular quality assessment methods are visual inspection, processing time, confusion-matrix based measures, mean square error (MSE)-based measures, and figure of merit (FOM). This survey also indicates that although most of the researchers only use a small number of test images (i.e., less than 10 test images), there are available datasets with a larger number of images for digital image segmentation that researchers can utilize. ? 2013 IEEE.

References

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