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Comparsion of Feature Extraction Methods for Finding Similar Images

  • Lukáš BurešEmail author
  • Filip Berka
  • Luděk Müller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10459)

Abstract

In this paper, we compare four methods of feature extraction for finding similar images. We created our own dataset which consists of 34500 colour images of various types of footwear and other accessories. We describe the methods that we experimented with and present results achieved with all of them. We presented the results to 23 people who then rated the performance of these methods. The best–rated method is selected for further research.

Keywords

Image similarity Feature extraction Local binary patterns Colour histogram Histogram of oriented gradients Convolution neural network 

Notes

Acknowledgment

This publication was supported by the project No. LO1506 of the Czech Ministry of Education, Youth and Sports, and by grant of the University of West Bohemia, project No. SGS-2016-039.

Computational resources were supplied by the Ministry of Education, Youth and Sports of the Czech Republic under the Projects CESNET (Project No. LM2015042) and CERIT-Scientific Cloud (Project No. LM2015085) provided within the program Projects of Large Research, Development and Innovations Infrastructures.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Faculty of Applied Sciences, New Technologies for the Information SocietyUniversity of West BohemiaPlzeňCzech Republic

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