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This article is cited in 11 scientific papers (total in 11 papers)
IMAGE PROCESSING, PATTERN RECOGNITION
On the quantitative performance evaluation of image analysis algorithms
P. P. Koltsov, A. S. Osipov, A. S. Kutsaev, A. A. Kravchenko, N. V. Kotovich, A. V. Zakharov Scientific-Research Institute for System Analysis, Russian Academy of Sciences
Abstract:
The paper contains a brief review of main approaches to the comparative performance evaluation of image analysis algorithms. Some empirical methods used for the comparative evaluation of edge detectors and image segmentation algorithms are considered and quantitative criteria employed in these methods are studied. Problems associated with the use of these criteria are described. Finally, using the edge detector evaluation as an example, we propose an empirical
method, called EDEM, which is implemented using our proprietary software system PICASSO.
Keywords:
comparative study, image analysis, edge detectors, image segmentation, performance measures, ground truth image, fuzzy sets.
Received: 20.04.2015 Revised: 22.07.2015
Citation:
P. P. Koltsov, A. S. Osipov, A. S. Kutsaev, A. A. Kravchenko, N. V. Kotovich, A. V. Zakharov, “On the quantitative performance evaluation of image analysis algorithms”, Computer Optics, 39:4 (2015), 542–556
Linking options:
https://www.mathnet.ru/eng/co16 https://www.mathnet.ru/eng/co/v39/i4/p542
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Abstract page: | 261 | Full-text PDF : | 259 | References: | 27 |
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