Authors: | Alamri, Faisal Žunić, Joviša |
Affiliations: | Mathematical Institute of the Serbian Academy of Sciences and Arts | Title: | Edge detection based on digital shape elongation measure | Journal: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Volume: | 10657 | First page: | 19 | Last page: | 27 | Issue Date: | 1-Jan-2018 | Rank: | M33 | ISBN: | 978-3-319-75192-4 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-319-75193-1_3 | Abstract: | In this paper, we justify the hypothesis that the methods based on the tools designed to cope with digital images can outperform the standard techniques, usually coming from differential calculus and differential geometry. Herein, we have employed the shape elongation measure, a well known shape based image analysis tool, to offer a solution to the edge detection problem. The shape elongation measure, as used in this paper, is a numerical characteristic of discrete shape, computable for all discrete point sets, including digital images. Such a measure does not involve any of the infinitesimal processes for its computation. The method proposed can be applied to any digital image directly, without the need of any pre-processing. |
Publisher: | Springer Link |
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