Dhingra, Shefali and Bansal, Poonam (2020) A Novel & Efficient Fusion Based Image Retrieval Model for Speedy Image Recovery. EAI Endorsed Transactions on Scalable Information Systems, 7 (27): e7. ISSN 2032-9407
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eai.9-3-2020.163832.pdf - Published Version Available under License Creative Commons Attribution No Derivatives. Download (3MB) | Preview |
Abstract
An efficient and novel image retrieval system is framed here, which retrieve images from massive datasets to overcome the constraints of efficiency and retrieval time. Thus to address this issue, an effective indexing technique is proposed on the hybrid system constituted by low level features of the image. Firstly, features are extracted from the combination color moment, LBP and segmentation to form a hybrid feature space. To reduce its dimensional space, principle component analysis is exercised which provide lesser and good quality features. On this space, two expedient indexing techniques are proposed: cluster based and similarity based. The approach that is proposed here is an innovative design of a hybrid content based image retrieval system, as in this framework all the skilled techniques are merged to form a competent and dynamic image retrieval system. Five touchstone datasets are used to test the performance of the system. Extensive experiments are carried out which shows that the system with cluster based indexing technique provides highlighted results as compared to similarity based technique and also surpasses the other latest state of art techniques in terms of precision and retrieval time.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Content based image retrieval, PCA, Clustering Based Indexing, Similarity-Based Indexing, Local binary pattern |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science QA75 Electronic computers. Computer science |
| Depositing User: | EAI Editor II. |
| Date Deposited: | 22 Oct 2020 12:32 |
| Last Modified: | 22 Oct 2020 12:32 |
| URI: | https://eprints.eudl.eu/id/eprint/727 |
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