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An improved similarity matching model for the content-based image retrieval model

Manimegalai Asokaraj

Manimegalai Asokaraj

  • Research Scholar, Visvesvaraya Technological UniversityBelagavi, India
  • Department of CSE, East Point College of Engineering and TechnologyBengaluru, India
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Asokaraj, Manimegalai
, 
Josephine Prem Kumar

Josephine Prem Kumar

Department of CSE, Cambridge Institute of TechnologyBengaluru, India
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Kumar, Josephine Prem
 et 
Nanda Ashwin

Nanda Ashwin

Department of CSE, East Point College of Engineering and TechnologyBengaluru,
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Ashwin, Nanda
  
19 juil. 2025
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Catégorie d'article: Research Article
Publié en ligne: 19 juil. 2025
Reçu: 30 août 2024
DOI: https://doi.org/10.2478/ijssis-2025-0031
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© 2025 Manimegalai Asokaraj et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

General workflow of CBIR.
General workflow of CBIR.

Figure 2:

Sample query image.
Sample query image.

Figure 3:

Result comparisons with different algorithms on the ROxford dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.
Result comparisons with different algorithms on the ROxford dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.

Figure 4:

Result comparisons with different algorithms on the RParis dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.
Result comparisons with different algorithms on the RParis dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.

Figure 5:

Comparison of computation time of different models on ROxford and RParis datasets. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.
Comparison of computation time of different models on ROxford and RParis datasets. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.

Comparison of precision and recall on the datasets

Method ROxford
 RParis
Precision Recall F1-Score Precision Recall F1-Score
CSM [18] 83.29 71 73.58 84.28 71.93 78.83
EP [19] 83.12 70.1 71.45 84.56 72.09 81.23
DCM [20] 79.12 65.1 61.45 80.09 69.01 75.41
GA-based IR [21] 84.16 66.6 78.56 85.56 72 74.51
IRT [22] 80.14 69.5 71.26 78.41 68.47 73.25
OHEM 85.56 73.3 81.45 86.25 75.59 87.89
Langue:
Anglais
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