Preprint Article Version 1 This version is not peer-reviewed

Hierarchical Image Retrieval by Multi-Feature Fusion

Version 1 : Received: 26 April 2017 / Approved: 26 April 2017 / Online: 26 April 2017 (18:51:42 CEST)

How to cite: Lu, X.; Wang, J.; Hou, Y.; Yang, M.; Wang, Q.; Zhang, X. Hierarchical Image Retrieval by Multi-Feature Fusion. Preprints 2017, 2017040174 (doi: 10.20944/preprints201704.0174.v1). Lu, X.; Wang, J.; Hou, Y.; Yang, M.; Wang, Q.; Zhang, X. Hierarchical Image Retrieval by Multi-Feature Fusion. Preprints 2017, 2017040174 (doi: 10.20944/preprints201704.0174.v1).

Abstract

Aiming at the problems that are poor generalization performance, low retrieval accuracy and large time consumption of existing content-based image retrieval system, the hierarchical image retrieval method based on multi feature fusion is proposed in this paper. The retrieval accuracy rates on Corel5K, UKbeach and Holidays are 68.23(Top 1), 3.73(N-S) and 88.20(mAp), respectively. The experimental results show that the method proposed in this paper can effectively improve the deficiency of single feature retrieval and save time significantly in the premise of a small amount of loss of accuracy.

Subject Areas

Hierarchical search; Image retrieval; Multi-feature fusion

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