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Feline eye–inspired artificial vision for enhanced camouflage breaking under diverse light conditions

Min Su Kim, Min Seok Kim, Mincheol Lee, Hyuk Jae Jang, Do Hyeon Kim, Sehui Chang, Hyojin Cho, Jiwon Kang, Changsoon Choi, Jung Pyo Hong, Do Kyung Hwang, Gil Ju Lee, Dae‐Hyeong Kim, Young Min Song

Year
2024
Citations
35

Abstract

Biologically inspired artificial vision research has led to innovative robotic vision systems with low optical aberration, wide field of view, and compact form factor. However, challenges persist in object detection and recognition against complex backgrounds and varied lighting. Inspired by the feline eye, which features a vertically elongated pupil and tapetum lucidum, this study introduces an artificial vision system designed for superior object detection and recognition in a monocular framework. Using a slit-like elliptical aperture and a patterned metal reflector beneath a hemispherical silicon photodiode array, the system reduces excessive light and enhances photosensitivity. This design achieves clear focus under bright light and enhanced sensitivity in dim conditions. Theoretical and experimental analyses demonstrate the system's ability to filter redundant information and detect camouflaged objects in diverse lighting, representing a substantial advancement in monocular camera technology and the potential of biomimicry in optical innovations.

Keywords

CamouflageArtificial intelligenceComputer visionComputer scienceBiomimeticsMachine visionOpticsMonocular visionFocus (optics)Photodiode

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