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Image retrieval using a scale-invariant feature transform bag-of-features model with salient object detection

Image retrieval using a scale-invariant feature transform bag-of-features model with salient... How to effectively retrieve digital images is a focus of image retrieval research. Developed in the 1990s, content-based image retrieval (CBIR) systems are used to extract low-level visual features. However, semantic gaps exist between these features and high-level semantic concepts. This study proposes an image retrieval solution based on a bag-of-features (BoF) model integrated with scale-invariant feature transform (SIFT) and salient object detection. An image search system based on this image retrieval solution, which used object images as the query image, was subsequently constructed. Overall, the results verify the feasibility of the object-based image retrieval solution. Finally, the enhanced image search method and precision enabled constructing an image search system. The system is expected to improve through the search pattern, as well as improve the accuracy of images search, images search system to make a real attempt to solve the huge amount of data and images search difficult problems arising. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Applied Systemic Studies Inderscience Publishers

Image retrieval using a scale-invariant feature transform bag-of-features model with salient object detection

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1751-0589
eISSN
1751-0597
DOI
10.1504/IJASS.2017.088903
Publisher site
See Article on Publisher Site

Abstract

How to effectively retrieve digital images is a focus of image retrieval research. Developed in the 1990s, content-based image retrieval (CBIR) systems are used to extract low-level visual features. However, semantic gaps exist between these features and high-level semantic concepts. This study proposes an image retrieval solution based on a bag-of-features (BoF) model integrated with scale-invariant feature transform (SIFT) and salient object detection. An image search system based on this image retrieval solution, which used object images as the query image, was subsequently constructed. Overall, the results verify the feasibility of the object-based image retrieval solution. Finally, the enhanced image search method and precision enabled constructing an image search system. The system is expected to improve through the search pattern, as well as improve the accuracy of images search, images search system to make a real attempt to solve the huge amount of data and images search difficult problems arising.

Journal

International Journal of Applied Systemic StudiesInderscience Publishers

Published: Jan 1, 2017

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