Fast and accurate near-duplicate image elimination for visual sensor networks
Currently, a huge amount of visual data such as digital images and videos have been collected by visual sensor nodes, that is, camera nodes, and distributed on visual sensor networks. Among the visual data, there are a lot of near-duplicate images, which cause a serious waste of limited storage, com...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717694172 |
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| _version_ | 1832553108086980608 |
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| author | Zhili Zhou QM Jonathan Wu Fang Huang Xingming Sun |
| author_facet | Zhili Zhou QM Jonathan Wu Fang Huang Xingming Sun |
| author_sort | Zhili Zhou |
| collection | DOAJ |
| description | Currently, a huge amount of visual data such as digital images and videos have been collected by visual sensor nodes, that is, camera nodes, and distributed on visual sensor networks. Among the visual data, there are a lot of near-duplicate images, which cause a serious waste of limited storage, computing, and transmission resources of visual sensor networks and a negative impact on users’ experience. Thus, near-duplicate image elimination is urgently demanded. This article proposes a fast and accurate near-duplicate elimination approach for visual sensor networks. First, a coarse-to-fine clustering method based on a combination of global feature and local feature is proposed to cluster near-duplicate images. Then in each near-duplicate group, we adopt PageRank algorithm to analyze the contextual relevance among images to select and reserve seed image and remove the others. The experimental results prove that the proposed approach achieves better performances in the aspects of both efficiency and accuracy compared with the state-of-the-art approaches. |
| format | Article |
| id | doaj-art-2aa1e6c00c49446fb062bd1ff8040d2d |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-2aa1e6c00c49446fb062bd1ff8040d2d2025-02-03T05:55:24ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-02-011310.1177/1550147717694172Fast and accurate near-duplicate image elimination for visual sensor networksZhili Zhou0QM Jonathan Wu1Fang Huang2Xingming Sun3Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, CanadaDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON, CanadaJiangsu Engineering Center of Network Monitoring & School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, ChinaJiangsu Engineering Center of Network Monitoring & School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, ChinaCurrently, a huge amount of visual data such as digital images and videos have been collected by visual sensor nodes, that is, camera nodes, and distributed on visual sensor networks. Among the visual data, there are a lot of near-duplicate images, which cause a serious waste of limited storage, computing, and transmission resources of visual sensor networks and a negative impact on users’ experience. Thus, near-duplicate image elimination is urgently demanded. This article proposes a fast and accurate near-duplicate elimination approach for visual sensor networks. First, a coarse-to-fine clustering method based on a combination of global feature and local feature is proposed to cluster near-duplicate images. Then in each near-duplicate group, we adopt PageRank algorithm to analyze the contextual relevance among images to select and reserve seed image and remove the others. The experimental results prove that the proposed approach achieves better performances in the aspects of both efficiency and accuracy compared with the state-of-the-art approaches.https://doi.org/10.1177/1550147717694172 |
| spellingShingle | Zhili Zhou QM Jonathan Wu Fang Huang Xingming Sun Fast and accurate near-duplicate image elimination for visual sensor networks International Journal of Distributed Sensor Networks |
| title | Fast and accurate near-duplicate image elimination for visual sensor networks |
| title_full | Fast and accurate near-duplicate image elimination for visual sensor networks |
| title_fullStr | Fast and accurate near-duplicate image elimination for visual sensor networks |
| title_full_unstemmed | Fast and accurate near-duplicate image elimination for visual sensor networks |
| title_short | Fast and accurate near-duplicate image elimination for visual sensor networks |
| title_sort | fast and accurate near duplicate image elimination for visual sensor networks |
| url | https://doi.org/10.1177/1550147717694172 |
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