Vadim Glezer’s modules model is a possible basis of vision perception description

For Russian citation (Opticheskii Zhurnal):

Бондарко В.М. Модель модулей В.Д. Глезера — возможная основа для описания зрительного восприятия // Оптический журнал. 2024. Т. 91. № 8. С. 99–109. http://doi.org/10.17586/1023-5086-2024-91-08-99-109

Bondarko V.M. Vadim Glezer’s modules model is a possible basis of vision perception description [in Russian] // Opticheskii Zhurnal. 2024. V. 91. № 8. P. 99–109. http://doi.org/10.17586/1023-5086-2024-91-08-99-109

For citation (Journal of Optical Technology):

Abstract:

Subject of study. The mechanisms of visual perception were studied. Aim of study is to determine a possibility of using the modules model to describe visual perception. This model was proposed by V.D. Glezer on the basis of obtained electrophysiological data. Method. Psychophysical methods and modeling were used. Experiments were carried out on image recognition and size estimation of spatial intervals and circles in the Delboeuf and Ebbinghaus illusions. The experimental data were fitted by models using full image spectra and a modules model in which the images were decomposed into finite Fourier series. For each image, a module of the optimal size was selected to save the most of the energy in the image. Two combinations of such modules were considered. Main results. It was shown that the optimal module size depended on image. Recognition images errors and their proximity estimations correlate with the distances between images calculated in the feature space as the norm of the difference their spectra, and partially with the distances obtained in one of the variants of the modules model. The modules model adequately approximated the segmentation and size estimation data, which was confirmed by the analysis of the paintings. Thus, the module model can describe the mechanisms of size estimation and segmentation. At the same time, for recognition it is necessary to improve this model: to introduce interaction between modules of different sizes. Therefore, the module model can be considered as a first approximation to the description of visual perception. Practical significance. The modules model can be used to analyze images and create artificial neural networks that provide segmentation and object recognition.

Keywords:

recognition, size estimation, segmentation, modeling, spatial frequency analysis, modules model, optical illusions

Acknowledgements:

the study was supported by the State funding allocated to the Pavlov Institute of Physiology Russian Academy of Sciences (№ 1021062411653-4-3.1.8).

OCIS codes: 330.7326, 330.4060, 330.5510, 330.5370

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