Search by Image Engine using Local Feature Detectors
| Autor: | Anastasiya Chupryna, Maksym Kolisnyk, Kirill Smelyakov, Oleksandr Ponomarenko |
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| Rok vydání: | 2020 |
| Předmět: |
business.industry
Computer science Big data Detector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Effective management computer.software_genre Experimental research Search engine Computer Science::Computer Vision and Pattern Recognition Data mining Image transformation Invariant (mathematics) business computer Transformation geometry |
| Zdroj: | 2020 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream). |
| DOI: | 10.1109/estream50540.2020.9108884 |
| Popis: | Nowadays, modern big data warehouses require the development of effective management algorithms. For large image storages first of all it's important to develop effective algorithms for comparing and searching a similar image from an image, taking into account their possible geometric transformations. In this regard, one of the most promising is the approach based on the use of invariant Local Feature Detectors. The work is carried out experimental research of such detectors’ effectiveness for Search by Image Engine in large image storages. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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