A.V. Bogoslovsky1, S.V. Vasilyev2, I.V. Zhigulina3

1-3 MESC AF «N.E. Zhukovsky and Y.A. Gagarin Air Force Academy» (Voronezh, Russia)
1 p-digim@mail.ru, 2 stanislav-vas1986@mail.ru, 3 ira_zhigulina@mail.ru

One of the most critical properties of biological vision is its division into central and peripheral components. Central vision offers high resolution but is not responsible for spatial orientation within the environment. In contrast, peripheral vision, while characterized by lower resolution, plays a vital role in the biological visual system by determining the subject’s position in the world and enabling rapid responses to objects appearing in the visual field. A defining feature of peripheral vision is its ability to quickly and accurately detect emerging objects, determining their direction of appearance, size, and speed of movement. These capabilities are dictated by the structural specifics of the retina and must be accounted for in the design of machine vision systems. Currently, machine vision systems do not treat peripheral processing as a distinct function, despite the clear priority of monitoring peripheral space. Equipping such systems with analogous capabilities requires the development of algorithmic software that is efficient according to the "detection accuracy versus detection time" criterion. This problem can be addressed using the phase-energy characteristics of images (video frames), which represent the amplitudes of spatial harmonics in the phase-energy spectrum. The inter-frame increments of these characteristics, known as phase-energy functions, exhibit high sensitivity at the edges of the visual field. This makes them suitable for processing peripheral regions of video frames, specifically for detecting objects that enter the image through its boundaries. The aim of this work is to investigate the potential of peripheral processing for video sequences. We have identified the characteristic properties of phase-energy functions in the peripheral areas of frames. The study demonstrates the possibility of using a reconfigurable peripheral zone to locate object appearances, determine their size, and estimate inter-frame displacement. It is also shown that object registration using phase-energy functions remains effective even when frame resolution is reduced by removing rows or columns at its edges. Furthermore, partitioning the peripheral area into horizontal and vertical segments for parallel processing significantly reduces the impact of noise on the phase-energy functions. The research findings are illustrated using both test and real-world video sequences. The results obtained from processing real-world sequences show that the detection capabilities of phase-energy functions are preserved even when the resolution of the frame's peripheral area is reduced by 50%, leading to lower computational costs. The proposed model for peripheral processing can be utilized in developing fast motion detection algorithms for the edges of the sensor field of view in various technical control and security systems, including those designed for monitoring dynamic objects.

Bogoslovsky A.V., Vasilyev S.V., Zhigulina I.V. Peripheral video signal processing. Achieve­ments of modern radioelectronics. 2026. V. 80. № 4. P. 88–97. DOI: https://doi.org/10.18127/j20700784-202604-09 [in Russian]

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