Abstract
Recognition of textures is one of the topical tasks of computer vision. The key step in solving this problem is the formation of feature description of the texture image. A new approach to the formation of texture features based on the theory of active perception is proposed. The results of a computational experiment based on the Brodatz-32 database are presented, and the accuracy of the classification is demonstrated. The application of the proposed feature systems for recognition of snow and land textures in the solution of the problem of auto piloting in complex natural and climatic conditions is considered.
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References
Rosniza, R., Nursuriati, J.: Texture feature extraction using 2-D Gabor Filters. In: IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2012, pp. 173–178 (2012)
Chen, J., Kellokumpu, V., Zhao, G., Pietikinen, M.: RLBP: robust local binary pattern. In: Proceedings of the British Machine Vision Conference (2013)
Sharma, G., Hussain, S., Jurie, F.: Local higher-order statistics (LHS) for texture categorization and facial analysis. Lecture Notes in Computer Science, vol. 7578. Springer, Heidelberg (2012)
Utrobin, V.A.: Physical interpretation of the elements of image algebra. Phys. Usp. 47, 1017–1032 (2004)
Hafemann, L.G.: An analysis of deep neural networks for texture classification. Dissertation presented as partial requisite to obtain the Masters degree, Curitbia, Brazil (2014)
Acknowledgements
The work was carried out at the NNSTU named after R. E. Alekseev, with the financial support of the Ministry of Education and Science of the Russian Federation under the agreement 14.577.21.0222 of 03.10.2016. Identification number of the project: RFMEFI57716X0222. Theme: “Creation of an experimental sample of an amphibious autonomous transport and technological complex with an intelligent control and navigation system for year-round exploration and drilling operations on the Arctic shelf.”
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Gai, V., Rodionov, P., Derbasov, M., Lyakhmanov, D., Koshurina, A. (2018). Texture Recognition from Positions of the Theory of Active Perceptions. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research. NEUROINFORMATICS 2017. Studies in Computational Intelligence, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-66604-4_15
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DOI: https://doi.org/10.1007/978-3-319-66604-4_15
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