Mr. Lukas De Greve Profile

Lukas De Greve

at Flanders Make

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Proceedings Article | 20 June 2024 Presentation + Paper

Digital twin for a task-driven multispectral camera design

Wenzhi Liao, Gerardo José Mora Jimena, Lukas De Greve, Abdellatif Bey-Temsamani, Bart De Ketelaere

Proceedings Volume 12999, 129991C (2024) https://doi.org/10.1117/12.3022296

KEYWORDS: Cameras, Tunable filters, Optical filters, Hyperspectral imaging, Image filtering, Digital imaging, Design, Image classification, Line scan image sensors, Image storage

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Spectral imaging allows seeing subtle optical signatures or light wavelengths invisible for human vision. This has potential for numerous industrial applications and a large economic impact by improving quality inspection, increasing automation and the development of innovative applications. However, current commercial spectral imaging systems (both hyper- and multi- spectral) are either too expensive or inflexible to be used in industrial applications (especially for SMEs: small and medium-sized enterprises), whereas standard RGB cameras are often difficult and mostly impractical to classify those materials that are looking visually similar (e.g., real and fake leaves with similar color, shape, texture). In this paper, we propose a new framework for a multispectral camera design. In particular, we first build a digital twin to simulate the output of a camera given a hardware configuration and details on the scene/object, then we optimize the wavelengths according to a specific application defined by end-users for the best filters selections. By combining the filters, illumination, sensor, lenses, pixel size, etc. from digital twin and optimization, we finally design a multispectral camera for the end-users, which provides a low-cost, flexible solution for industrial users. Experimental results from material classification show that our multispectral camera with 3 spectral bands can achieve similar performances as hyperspectral camera on real leaves separation.

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