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Finding Image Semantics from a Hierarchical Image Database Based on Adaptively Combined Visual Features

  • Pritee Khanna
  • Shreelekha Pandey
  • Haruo Yokota
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8055)

Abstract

Correlating image semantics with its low level features is a challenging task. Although, humans are adept in distinguishing object categories, both in visual as well as in semantic space, but to accomplish this computationally is yet to be fully explored. The learning based techniques do minimize the semantic gap, but unlimited possible categorization of objects in real world is a major challenge to these techniques. This work analyzes and utilizes the strength of a semantically categorized image database to assign semantics to query images. Semantics based categorization of images would result in image hierarchy. The algorithms proposed in this work exploit visual image descriptors and similarity measures in the context of a semantically categorized image database. A novel ‘Branch Selection Algorithm’ is developed for a highly categorized and dense image database, which drastically reduces the search space. The search space so obtained is further reduced by applying any one of the four proposed ‘Pruning Algorithms’. Pruning algorithms maintain accuracy while reducing the search space. These algorithms use an adaptive combination of multiple visual features of an image database to find semantics of query images. Branch Selection Algorithm tested on a subset of ‘ImageNet’ database reduces search space by 75%. The best pruning algorithm further reduces this search space by 26% while maintaining 95% accuracy.

Keywords

Discrete Cosine Transform Image Retrieval Semantic Similarity Image Database Query Image 
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 2013

Authors and Affiliations

  • Pritee Khanna
    • 1
  • Shreelekha Pandey
    • 1
  • Haruo Yokota
    • 2
  1. 1.Design and Manufacturing JabalpurPDPM Indian Institute of Information TechnologyJabalpurIndia
  2. 2.Graduate School of Information Science and EngineeringTokyo Institute of TechnologyMeguro-kuJapan

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