Semantic Based Image Retrieval System for Web Images

  • K. K. UmeshEmail author
  • Suresha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 178)


In this research, we have proposed semantic based image retrieval system to retrieve set of relevant images for the given query image from the Web. We have used global color space model and Dense SIFT feature extraction technique to generate visual dictionary using clustering algorithm. The images are transformed into set of features. These features are used as inputs in Self Organizing Maps (SOM) to train the nodes for generating the code word to form visual dictionary. These codewords are used to represent images semantically to form visual labels using Bag-of-Features (BoF). The Histogram intersection method is used to measure the distance between input image and the set of images in the image database to retrieve similar images. The experimental results are evaluated over a collection of 1000 generic Web images to demonstrate the effectiveness of the proposed system.


Content-based image retrieval Dense SIFT feature Self-Organizing Map Bag-of-Features Bag-of-Words Similarity measure 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Information Science and EngineeringS J College of EngineeringMysoreIndia
  2. 2.Department of Studies in Computer ScienceMysore UniversityMysoreIndia

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