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Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8–9, 2021, Proceedings, Part II

Research Article

Content-Based Image Retrieval Using Local Derivative Laplacian Co-occurrence Pattern

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  • @INPROCEEDINGS{10.1007/978-3-030-82565-2_33,
        author={Prashant Srivastava and Manish Khare and Ashish Khare},
        title={Content-Based Image Retrieval Using Local Derivative Laplacian Co-occurrence Pattern},
        proceedings={Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8--9, 2021, Proceedings, Part II},
        proceedings_a={ICMTEL PART 2},
        year={2021},
        month={7},
        keywords={CBIR Image retrieval Laplacian of Gaussian Local Derivative Pattern Gray-Level Co-occurrence pattern},
        doi={10.1007/978-3-030-82565-2_33}
    }
    
  • Prashant Srivastava
    Manish Khare
    Ashish Khare
    Year: 2021
    Content-Based Image Retrieval Using Local Derivative Laplacian Co-occurrence Pattern
    ICMTEL PART 2
    Springer
    DOI: 10.1007/978-3-030-82565-2_33
Prashant Srivastava1,*, Manish Khare2, Ashish Khare3
  • 1: NIIT University
  • 2: Dhirubhai Ambani Institute of Information and Communication Technology
  • 3: Department of Electronics and Communication, University of Allahabad
*Contact email: prashant.jk087@gmail.com

Abstract

For accessing images from huge repository in an easy manner, the images are required to be properly indexed. Content-Based Image Retrieval (CBIR) is a field which deals with finding solutions to such problems. This paper proposes a new multiresolution descriptor namely, Local Derivative Laplacian Co-occurrence Pattern (LDLCP) for CBIR. Gray level image is subjected to four-level Laplacian of Gaussian filtering in order to perform multiresolution processing of image. Local Derivative Pattern descriptors of resulting four-level filtered image is computed to extract local information from the image. Finally, the Gray-Level Co-occurrence Matrix is used for constructing feature vector. Corel-1K and Corel-5K datasets have been used to test the proposed descriptor and its performance is measured using precision and recall metrics.

Keywords
CBIR Image retrieval Laplacian of Gaussian Local Derivative Pattern Gray-Level Co-occurrence pattern
Published
2021-07-21
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-82565-2_33
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