On the quantitative performance evaluation of image analysis algorithms
Автор: Koltsov Piotr Petrovich, Osipov Andrey Sergeevich, Koutsaev Aleksandr Sergeevich, Kravchenko Aleksandr Anatolevich, Kotovich Nikolay Vladimirovich, Zakharov Aleksei Viktorovich
Журнал: Компьютерная оптика @computer-optics
Рубрика: Обработка изображений: Восстановление изображений, выявление признаков, распознавание образов
Статья в выпуске: 4 т.39, 2015 года.
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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.
Ground truth образ, comparative study, image analysis, edge detectors, image segmentation, performance measures, ground truth image, fuzzy sets
Короткий адрес: https://sciup.org/14059395
IDR: 14059395 | DOI: 10.18287/0134-2452-2015-39-4-542-556