On the Application of Orthogonal Series Density Estimation for Image Classification Based on Feature Description

  • Piotr Duda
  • Maciej Jaworski
  • Lena Pietruczuk
  • Marcin Korytkowski
  • Marcin Gabryel
  • Rafał Scherer
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 364)

Abstract

This paper presents an image classification algorithm called density-based classifier. The proposed method puts together the image representation based on keypoints and the estimation of the probability density of descriptors with the application of orthonormal series. For each class of images a separate classifier is constructed. The presented procedure ensures that different descriptors affect the final decision in a different degree. The trained classifier determines whether the query image is assigned to the class or not. The obtained experimental results show that proposed method provides good results. The algorithm can be applied to many tasks in the field of image processing.

Keywords

Content-based image retrieval Image classification 

Notes

Acknowledgments

The project was funded by the National Center for Science under decision number DEC-2011/01/D/ST6/06957.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Piotr Duda
    • 1
  • Maciej Jaworski
    • 1
  • Lena Pietruczuk
    • 1
  • Marcin Korytkowski
    • 1
  • Marcin Gabryel
    • 1
  • Rafał Scherer
    • 1
  1. 1.Institute of Computational IntelligenceCzestochowa University of TechnologyCzestochowaPoland

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