Image curvature assessment in the presence of distractors

Subject of study. The mechanisms of visual perception of image curvature in the presence of additional images, referred to as distractors, were investigated. Aim of study. The aim was to describe and analyze the mechanisms of image curvature perception. Method. A series of psychophysical experiments were conducted, wherein images were analyzed, and the results were compared with those of prior studies on the perception of other visual stimuli. Main results. Curvatures for both real and interpolated images were estimated. Distortions (illusions) in the perception of image curvature in the presence of distractors were identified. Straight lines were perceived as curved, and the estimates for other stimuli were also erroneous. These illusions were more pronounced for interpolated images. The obtained data are consistent with the tilt illusion arising from the interaction between spatial-frequency channels. The observed illusions of image curvature may also be hypothetically explained by this interaction. However, a comparison with the perception of curvature of other images indicates ambiguity in the mechanisms for estimating curvature, as well as their dependence on the shape of the images and the surroundings. Practical significance. These findings can be applied in artificial neural networks for facial recognition and other images similar to those studied, as the initial processing of objects in such networks often involves filtering similar to that performed by the receptive fields of the visual cortex.

Authors

Institutions

Publication Details

Journal
Journal of Optical Technology
Published
2024-10-01
DOI
https://doi.org/10.1364/jot.91.000696
Primary Topic
Medical Image Segmentation Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Image curvature assessment in the presence of distractors

V. M. Bondarko, V. N. Chikhman, С. Д. Солнушкин
Journal of Optical Technology
Medical Image Segmentation Techniques
article

Image curvature assessment in the presence of distractors

V. M. Bondarko, V. N. Chikhman, С. Д. Солнушкин
article en

Abstract

Subject of study. The mechanisms of visual perception of image curvature in the presence of additional images, referred to as distractors, were investigated. Aim of study. The aim was to describe and analyze the mechanisms of image curvature perception. Method. A series of psychophysical experiments were conducted, wherein images were analyzed, and the results were compared with those of prior studies on the perception of other visual stimuli. Main results. Curvatures for both real and interpolated images were estimated. Distortions (illusions) in the perception of image curvature in the presence of distractors were identified. Straight lines were perceived as curved, and the estimates for other stimuli were also erroneous. These illusions were more pronounced for interpolated images. The obtained data are consistent with the tilt illusion arising from the interaction between spatial-frequency channels. The observed illusions of image curvature may also be hypothetically explained by this interaction. However, a comparison with the perception of curvature of other images indicates ambiguity in the mechanisms for estimating curvature, as well as their dependence on the shape of the images and the surroundings. Practical significance. These findings can be applied in artificial neural networks for facial recognition and other images similar to those studied, as the initial processing of objects in such networks often involves filtering similar to that performed by the receptive fields of the visual cortex.

Journal of Optical TechnologyVol. 91(10)
Pavlov Institute of Physiology of the Russian Academy of Sciences (RU)
Russian Academy of Sciences
Openalex Percentile: Top 70%
Medical Image Segmentation Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.