About Edge Detection in Digital Images
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Edge detection is one of the most commonly used procedures in digital image processing. In the last 30-40 years, many methods and algorithms for edge detection have been proposed. This article presents an overview of edge detection methods, the methods are divided according to the applied basic principles. Next, the measures and image database used for edge detectors performance quantification are described. Ordinary users as well as authors proposing new edge detectors often use Matlab function without understanding it in details. Therefore, one chapter is devoted to some of Matlab function parameters that affect the final result. Finally, the latest trends in edge detection are listed. Picture Lena and two images from Berkeley segmentation data set (BSDS500) are used for edge detection methods comparison.
KeywordsImage processing, edge detection, gradient operator, morphological operator, fractional differentiation, Berkeley segmentation data set (BSDS), NYU depth dataset, Matlab
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2018 vol. 27, č. 4, s. 919-929. ISSN 1210-2512
- 2018/4