Robust content-based image searches for copyright protection

ABSTRACT

This paper proposes a novel content-based image retrieval scheme for image copy identification. Its goal is to detect matches between a set of doubtful images and the ones stored in the database of the legal holders of the photographies. If an image was stolen and used to create a pirated copy, it tries to identify from which original image that copy was created. The image recognition scheme is based on local differential descriptors. Therefore, the matching process takes into account a large set of variations that might have been applied to stolen images in order to create pirated copies. The high cost and the complexity of this image recognition scheme requires a very efficient retrieval process since many individual queries must be executed before being able to construct the final result. This paper therefore proposes to use a novel search method that trades the precision of each individual search for reduced query execution time. This imprecision has only little impact on the overall recognition performance since the final result is a consolidation of many partial results. However, it dramatically accelerates queries. This result has then been corroborated by a theoretically study. Experiments show the efficiency and the robustness of the proposed scheme.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Image databases

Additional Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.9 Applications

General Terms:
Algorithms, Experimentation, Performance

Keywords:
approximate nearest-neighbor searches, content-based image retrieval, copyright protection, fine grain, recognition