Pareto-Depth for Multiple-Query Image Retrieval

Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.

  • Project Category : IEEE Projects
  • Project Year : 2015-2016
  • Department
  • B.E(Computer Science) , B.E(Electronics and Communication), B.E(Information Technology), B.SC(CS), B.SC(IT), B.Tech, BCA, M.E(APPLIED ELECTRONICS), M.E(Computer Science), M.E(SOFTWATE ENGG), M.SC(CS&M), M.SC(CS), M.SC(IT), M.SC(SOFTWARE ENGG), M.Tech, MCA,
  • Domain
  • computer application, Digital Image Processing, Image Processing, MATLAB Projects,
  • Technology
  • Image processing, matlab,
  • Avilable city
  • Ahmedabad, Bangalore, Chennai, Coimbatore, Davangere, Delhi, Dharmapuri, Ernakulam, Hyderabad, Kolkata, Kozhikode, Madurai, Mumbai, Pondicherry, Pune, Salem, Thanjavur, Tirunelveli, Trichy, Vellore,

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