An image-based multimedia database and efficient detection though features
Accurate feature detection during Image retrieval is important, data retrieves through image retrieval methods like CBIR and CBIR higher dimension data also need storage and access through different methods, content-based Image retrieval uses query like query by feature and query by example. More fo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
VFAST-Research Platform
2019
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/88354/1/MohdShafrymohdRahim2019_AnImagebasedMultimediaDatabase.pdf http://eprints.utm.my/id/eprint/88354/ http://dx.doi.org/10.21015/vtse.v14i1.536 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | Accurate feature detection during Image retrieval is important, data retrieves through image retrieval methods like CBIR and CBIR higher dimension data also need storage and access through different methods, content-based Image retrieval uses query like query by feature and query by example. More focus has made on accurate feature detection because need accurate feature retrieval. In simple words objectives are, to develop methods with sequence to classify features with normalization for efficient image retrieval from bulk dataset and also to improve method for local and global feature retrieval with automatic feature detection along accuracy. After study of different detection-based system, a methodology has been proposed which improves retrieval based on feature detection and feature detection had been improve with combination DWT+PCA+KSVM (polygon kernel +RBF kernel + Linear Kernel). |
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