A model of image retrieval based on KD-Tree Random Forest
Data Technologies and Applications
ISSN: 2514-9288
Article publication date: 5 May 2023
Issue publication date: 20 October 2023
Abstract
Purpose
The problem of image retrieval and image description exists in various fields. In this paper, a model of content-based image retrieval and image content extraction based on the KD-Tree structure was proposed.
Design/methodology/approach
A Random Forest structure was built to classify the objects on each image on the basis of the balanced multibranch KD-Tree structure. From that purpose, a KD-Tree structure was generated by the Random Forest to retrieve a set of similar images for an input image. A KD-Tree structure is applied to determine a relationship word at leaves to extract the relationship between objects on an input image. An input image content is described based on class names and relationships between objects.
Findings
A model of image retrieval and image content extraction was proposed based on the proposed theoretical basis; simultaneously, the experiment was built on multi-object image datasets including Microsoft COCO and Flickr with an average image retrieval precision of 0.9028 and 0.9163, respectively. The experimental results were compared with those of other works on the same image dataset to demonstrate the effectiveness of the proposed method.
Originality/value
A balanced multibranch KD-Tree structure was built to apply to relationship classification on the basis of the original KD-Tree structure. Then, KD-Tree Random Forest was built to improve the classifier performance and retrieve a set of similar images for an input image. Concurrently, the image content was described in the process of combining class names and relationships between objects.
Keywords
Acknowledgements
The authors would like to thank the Faculty of Information Technology, University of Sciences, Hue University, Hue, Vietnam, for their professional advice for this study. They would also like to thank HCMC University of Food Industry, HCMC University of Education and University of Economics – The University of Danang, Vietnam. They also thank anonymous reviewers for their helpful comments on this paper
Funding: This work has been sponsored and funded by the Ho Chi Minh City University of Food Industry under the Contract No. 147/HD-DCT.
Citation
Dinh, N.T., Nhi, N.T.U., Le, T.M. and Van, T.T. (2023), "A model of image retrieval based on KD-Tree Random Forest", Data Technologies and Applications, Vol. 57 No. 4, pp. 514-536. https://doi.org/10.1108/DTA-06-2022-0247
Publisher
:Emerald Publishing Limited
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