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Content-based blur image retrieval using quaternion approach and frequency adder LBP

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Abstract

The paper presents a content based image retrieval scheme based on feature extraction and weighing. Features are extracted using frequency adder based local binary pattern and blur detection metric which are then optimally combined using a weighing scheme. Simulations are performed on modified Wang and KTH-TIPS databases, which include images from four different classes of blur respectively. Comparison of simulation results with the state-of-the-art techniques show better retrieval precision and recall values for proposed technique.

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Authors and Affiliations

  1. National University of Sciences and Technology, Islamabad, Pakistan

    Komal Nain Sukhia & Abdul Ghafoor

  2. COMSATS University, Islamabad, Pakistan

    M. Mohsin Riaz

Authors
  1. Komal Nain Sukhia
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  2. M. Mohsin Riaz
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  3. Abdul Ghafoor
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Correspondence to Abdul Ghafoor.

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Sukhia, K.N., Riaz, M.M. & Ghafoor, A. Content-based blur image retrieval using quaternion approach and frequency adder LBP. Multidim Syst Sign Process 30, 2167–2183 (2019). https://doi.org/10.1007/s11045-019-00643-w

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  • DOI: https://doi.org/10.1007/s11045-019-00643-w

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