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  • Thanh The Van,
  • Thanh Le,
  • Nguyen Thi Dinh
Thanh The Van
Ho Chi Minh City University of Education

Corresponding Author:[email protected]

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Thanh Le
Hue University University of Sciences
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Nguyen Thi Dinh
Hue University University of Sciences
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The paper proposes an alternative approach to improve the performance of image retrieval. In this work, a framework for image retrieval based on machine learning and semantic retrieval is proposed. In the preprocessing phase, the image is segmented objects by using Graph-cut, and the feature vectors of objects presented in the image and their visual relationships are extracted using R-CNN. The feature vectors, visual relationships, and their symbolic labels are stored in KD-Tree data structures which can be used to predict the label of objects and visual relationships later. To facilitate semantic query, the images use the RDF data model and create an ontology for the symbolic labels annotated. For each query image, after extracting their feature vectors, the KD-Tree is used to classify the objects and predict their relationship. After that, a SPARQL query is built to extract a set of similar images. The SPARQL query consists of triple statements describing the objects and their relationship which were previously predicted. The evaluation of the framework with the MS-COCO dataset and Flickr showed that the precision achieved scores of 0.9218 and 0.9370 respectively.
17 Mar 2023Submitted to Expert Systems
27 Mar 2023Submission Checks Completed
27 Mar 2023Assigned to Editor
02 Apr 2023Reviewer(s) Assigned
01 May 2023Review(s) Completed, Editorial Evaluation Pending
01 May 2023Editorial Decision: Revise Minor
23 May 20231st Revision Received
30 May 2023Submission Checks Completed
30 May 2023Assigned to Editor
01 Jun 2023Reviewer(s) Assigned
23 Jun 2023Review(s) Completed, Editorial Evaluation Pending
27 Jun 2023Editorial Decision: Accept