SPECTRAL ALGORITHM FOR CONTENT-BASED IMAGE RETRIEVAL

Authors

  • Hanan A. Al-Jubouri Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq Author
  • Sawsan M. Mahmmod Computer Engineering Department, Mustansiriyah University, Baghdad, Iraq Author

DOI:

https://doi.org/10.31272/jeasd.24.5.6

Keywords:

Content-Based Image Retrieval, Local Binary Pattern, Discrete Cosine Transform, data-level fusion, score-level fusion

Abstract

Colour images are rich in visual information. The process of searching for the most similar images in large-scale database based on visual features of query image is still a challenge in Content-Based Image Retrieval (CBIR) due to a semantic gap issue. In this paper, we proposed a fusing retrieval method to diminish the gap between high-level and low-level meanings by involving two aspects. The first aspect is increasing the effectiveness of image representation. Hence, data-level fusion features were suggested, a local feature from Discrete Cosine Transform (DCT) and Local Binary Patterns (LBP) in frequency and spatial domains respectively that was applied by a spectral clustering algorithm (graph-based) in addition to a global weighted LBP feature. The second aspect is fusing multiple retrieved similarity measures (scores/evidences) obtained from above global (LBP) and local features (DCTLBP) in terms of score-level fusion. The method is evaluated in WANG standard publically dataset.

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Published

2020-09-01

Issue

Vol. 24 No. 5 (2020): Journal of Engineering and Sustainable Development

Section

Articles

License

Creative Commons License

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How to Cite

SPECTRAL ALGORITHM FOR CONTENT-BASED IMAGE RETRIEVAL. (2020). Journal of Engineering and Sustainable Development, 24(5), 37-49. https://doi.org/10.31272/jeasd.24.5.6