Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers

Research Article

Fuzzy Approach for Image Near-Duplicate Detection Using Gray Level Vertex Matching in Attribute Relational Bipartite Graphs

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  • @INPROCEEDINGS{10.1007/978-3-642-37949-9_35,
        author={Goutam Datta and Bushan Raina},
        title={Fuzzy Approach for Image Near-Duplicate Detection Using Gray Level Vertex Matching in Attribute Relational Bipartite Graphs},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers},
        proceedings_a={QSHINE},
        year={2013},
        month={7},
        keywords={ARBG IND Fuzzy ARBG BVT},
        doi={10.1007/978-3-642-37949-9_35}
    }
    
  • Goutam Datta
    Bushan Raina
    Year: 2013
    Fuzzy Approach for Image Near-Duplicate Detection Using Gray Level Vertex Matching in Attribute Relational Bipartite Graphs
    QSHINE
    Springer
    DOI: 10.1007/978-3-642-37949-9_35
Goutam Datta1,*, Bushan Raina1,*
  • 1: Lingaya’s University
*Contact email: gdatta1@yahoo.com, rbushan@rediffmail.com

Abstract

Shape of different regions of an image depends on the detection of the corners. .However vague information such as blurring, noise etc in an image is normally due to missing curvatures in the regions of image and therefore for the reliable decision for the detection of images in the corresponding domains based on corners in gray level images of source image and its duplicate and for their equivalence we give an algorithm linking it to the set theoretic fuzzy technique. We propose Attribute Relational Bipartite Graph (ARBG) for image near-duplicate (IND) as an important model. The application of the proposed algorithm works well as vertex detectors in their respective two domains. The performance is tested on a number of test images to show the efficiency of the fuzzy based algorithm.