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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. 1, pp. 886–893, June 2005
Jégou, H., Douze, M., Schmid, C.: Improving bag-of-features for large scale image search. Int. J. Comput. Vis. 87(3), 316–336 (2010)
Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Pereira, F., Burges, C.J.C., Bottou, L., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 25, pp. 1097–1105. Curran Associates, Inc., Red Hook (2012)
McConnell, R.: Method of and apparatus for pattern recognition, 28 January 1986. US Patent 4,567,610
Muja, M., Lowe, D.G.: Fast approximate nearest neighbors with automatic algorithm configuration. In: International Conference on Computer Vision Theory and Application VISSAPP 2009, pp. 331–340. INSTICC Press (2009)
Muramatsu, C., Takahashi, T., Morita, T., Endo, T., Fujita, H.: Similar image retrieval of breast masses on ultrasonography using subjective data and multidimensional scaling. In: Tingberg, A., Lång, K., Timberg, P. (eds.) IWDM 2016. LNCS, vol. 9699, pp. 43–50. Springer, Cham (2016). doi:10.1007/978-3-319-41546-8_6
Ojala, T., Pietikainen, M., Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recogn. 29(1), 51–59 (1996)
Pass, G., Zabih, R.: Comparing images using joint histograms. Multimedia Syst. 7(3), 234–240 (1999)
Pearson, K.: Contributions to the mathematical theory of evolution. Philos. Trans. R. Soc. Lond.: Math. Phys. Eng. Sci. 186, 343–414 (1895)
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Bureš, L., Berka, F., Müller, L. (2017). Comparsion of Feature Extraction Methods for Finding Similar Images. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2017. Lecture Notes in Computer Science(), vol 10459. Springer, Cham. https://doi.org/10.1007/978-3-319-66471-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-66471-2_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66470-5
Online ISBN: 978-3-319-66471-2
eBook Packages: Computer ScienceComputer Science (R0)