Content Based Image Retrieval Using Region Labelling

  • J. Naveen Kumar Reddy
  • Chakravarthy Bhagvati
  • S. Bapi Raju
  • Arun K. Pujari
  • B. L. Deekshatulu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4338)


This paper proposes a content based image retrieval system that uses semantic labels for determining image similarity. Thus, it aims to bridge the semantic gap between human perception and low-level features. Our approach works in two stages. Image segments, obtained from a subset of images in the database by an adaptive k-means clustering algorithm, are labelled manually during the training stage. The training information is used to label all the images in the database during the second stage. When a query is given, it is also segmented and each segment is labelled using the information available from the training stage. Similarity score between the query and a database image is based on the labels associated with the two images. Our results on two test databases show that region labelling helps in increasing the retrieval precision when compared to feature-based matching.


Image Retrieval Average Precision Query Image Relevance Feedback Content Base Image Retrieval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • J. Naveen Kumar Reddy
    • 1
  • Chakravarthy Bhagvati
    • 1
  • S. Bapi Raju
    • 1
  • Arun K. Pujari
    • 1
  • B. L. Deekshatulu
    • 1
  1. 1.Dept. of Computer and Information SciencesUniversity of HyderabadHyderabad

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