Bio-inspired approach to multistage image processing

Leonid I. Timchenko; Sergii V. Pavlov; Natalia I. Kokryatskaya; Anna A. Poplavska; Iryna M. Kobylyanska; Iryna I. Burdenyuk; Waldemar Wójcik; Svetlana Uvaysova; Zhassulan Orazbekov; Gulzhan Kashaganova

doi:10.1117/12.2280976

7 August 2017 Bio-inspired approach to multistage image processing

Leonid I. Timchenko, Sergii V. Pavlov, Natalia I. Kokryatskaya, Anna A. Poplavska, Iryna M. Kobylyanska, Iryna I. Burdenyuk, Waldemar Wójcik, Svetlana Uvaysova, Zhassulan Orazbekov, Gulzhan Kashaganova

Author Affiliations +

Proceedings Volume 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017; 104453M (2017) https://doi.org/10.1117/12.2280976
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2017, 2017, Wilga, Poland

Abstract

Multistage integration of visual information in the brain allows people to respond quickly to most significant stimuli while preserving the ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing, described in this paper, comprises main types of cortical multistage convergence. One of these types occurs within each visual pathway and the other between the pathways. This approach maps input images into a flexible hierarchy which reflects the complexity of the image data. The procedures of temporal image decomposition and hierarchy formation are described in mathematical terms. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image which encapsulates, in a computer manner, structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a very quick response from the system. The result is represented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match.

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Leonid I. Timchenko, Sergii V. Pavlov, Natalia I. Kokryatskaya, Anna A. Poplavska, Iryna M. Kobylyanska, Iryna I. Burdenyuk, Waldemar Wójcik, Svetlana Uvaysova, Zhassulan Orazbekov, and Gulzhan Kashaganova "Bio-inspired approach to multistage image processing", Proc. SPIE 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017, 104453M (7 August 2017); https://doi.org/10.1117/12.2280976

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