Developing a method to generate an adaptive real-time camouflage pattern based on electro-chromic active devices

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Authors

  • Nguyen Thanh Lam Institute of Technical Physics, Academy of Military Science and Technology
  • Nguyen Anh Tuan Institute of Technical Physics, Academy of Military Science and Technology
  • Nguyen Manh Thang (Corresponding Author) Academy of Military Science and Technology

DOI:

https://doi.org/10.54939/1859-1043.j.mst.99.2024.78-88

Keywords:

Camouflage patterns; Adaptive camouflage; CSI; UIQI.

Abstract

Traditional camouflage faces limitations in modern combat, especially with moving targets or rapidly changing backgrounds. Adaptive camouflage, which adjusts colors and patterns in real time, provides a more flexible and effective solution. This paper presents a comprehensive study of popular adaptive camouflage principles worldwide and proposes a camouflage model for the visible light spectrum based on active electro-chromic principles. Evaluation results indicate that adaptive patterns achieve the lowest Camouflage Similarity Index (CSI) and the highest Universal Image Quality Index (UIQI) across various backgrounds, demonstrating the clear effectiveness of the proposed model. With 3 to 5 dominant colors, pattern generation time is under 1 second, and adaptive patterns exhibit the highest similarity to the background compared to fixed patterns.

References

[1]. R.Rao, “Introduction to Camouflage and Deception,” Defence Scientific Information & Documentation Centrer, Defence R&D Organisation, Delhi-110054, pp. 119-126, (1999).

[2]. K. W. McKee, D. Tack, “Active Camouflage for Infantry Headwear Applications,” Humansystems Inc., Canada, (2007).

[3]. A. Schwarz, “Adaptive camouflage in the VIS and IR spectral range: main principles and mechanisms,” Proc. SPIE, vol. 9653, pp. 52-61, (2015). DOI: https://doi.org/10.1117/12.2195646

[4]. G. Santos et al., “Prototype of adaptive, multispectral camouflage for the soldier,” Proc.SPIE, vol. 11865, pp. 160-166, (2021). DOI: https://doi.org/10.1117/12.2600056

[5]. Nguyen Thu Cam et al., “Giáo trình ngụy trang nghi trang trong phòng chống trinh sát quang điện tử”, NXB Quân đội Nhân dân, tr. 112-120, (2023).

[6]. J. Lee et al., “Thermally Controlled, Active Imperceptible Artificial Skin in Visible-to-Infrared Range,” Adv. Funct. Mater., vol. 30, no. 36, pp. 2003328, (2020). DOI: https://doi.org/10.1002/adfm.202003328

[7]. G. Wang et al., “Mechanical Chameleon through Dynamic Real-Time Plasmonic Tuning,” ACS Nano, vol. 10, no. 2, pp. 1788-1794, (2016). DOI: https://doi.org/10.1021/acsnano.5b07472

[8]. Maarten A. Hogervorst, Margreet M. de Kok, “Demonstrator of adaptive visual camouflage based on LEDs,” Proc. SPIE, vol. 11865, pp. 149-159, (2021). DOI: https://doi.org/10.1117/12.2600172

[9]. V. K. Shrivastava et al, “Computer-aided diagnosis of psoriasis skin images with HOS, texture and color features: a first comparative study of its kind,” Computer methods and programs in biomedicine, vol. 126, pp. 98-109, (2016). DOI: https://doi.org/10.1016/j.cmpb.2015.11.013

[10]. N.C. Yang et al, “A fast MPEG-7 dominant color extraction with new similarity measure for image retrieval”, Vis. Commun. Image Represent., vol. 10, no. 2, pp. 92-105, (2008). DOI: https://doi.org/10.1016/j.jvcir.2007.05.003

[11]. Y. J. Yan et al, “Fusion of dominant colour and spatial layout features for effective image retrieval of coloured logos and trademarks,” IEEE international conference on multimedia big data, pp. 306-311, (2015), 10.1109/BigMM.2015.43 DOI: https://doi.org/10.1109/BigMM.2015.43

[12]. S. Bi et al. “Optical classification of inland waters based on an improved Fuzzy C-Means method,” Optics Express. vol. 27, no. 24, pp.34838-34856, (2019). DOI: https://doi.org/10.1364/OE.27.034838

[13]. C. J. Lin et al., “Developing a similarity index for static camouflaged target detection,” Imaging Sci. J., vol. 62, no. 6, pp. 337-341, (2014). DOI: https://doi.org/10.1179/1743131X13Y.0000000057

[14]. Tran Tien Bao et al., “A method to evaluate camouflage effectiveness by computer simulation,” JMST, vol. 90, pp. 119-126, (2023).

[15]. Z. Wang, A. C. Bovik, “A universal image quality index,” IEEE signal processing letters, vol. 9, no. 3, pp. 81-84, (2002). DOI: https://doi.org/10.1109/97.995823

[16]. Y. Byun et al., “Image fusion-based change detection for flood extent extraction using bi-temporal very high-resolution satellite images,” Remote Sensing, vol. 7, no. 8, pp. 10347-10363, (2015). DOI: https://doi.org/10.3390/rs70810347

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Published

25-11-2024

How to Cite

Nguyễn, T. L., A. T. Nguyen, and Nguyen Manh Thang. “Developing a Method to Generate an Adaptive Real-Time Camouflage Pattern Based on Electro-Chromic Active Devices”. Journal of Military Science and Technology, vol. 99, no. 99, Nov. 2024, pp. 78-88, doi:10.54939/1859-1043.j.mst.99.2024.78-88.

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Physics & Materials Science

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