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Camouflage Assessments with Digital Pattern Painting Based on the Multi-Scale Pattern-in-Picture Evaluation Model

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In general, traditional evaluations of target camouflage effects are usually conducted based on observational data and general results of statistical analysis. This widely applied methodology quantifies the detection and identification probabilities of camouflage objects but has considerable shortcomings. This data evaluation process is laborious and time-consuming and very low in reproducibility, which sheds light on the necessity of developing a more efficient method in this study field. The growth of computeraided image processing technology provides technical support for camouflage effect evaluation based on digital image processing. Digital pattern painting, which has been previously applied to combat utility uniforms, is a new methodology full of potential due to its broad geographical adaptability. This study proposes a multi-scale pattern-in-picture method to evaluate camouflage effects at different distances. We also established a computer-aided background image library and camouflage assessments with digital simulation and created an evaluation system that could be effectively applied to combat utility uniforms. More than 40 testers participated in this study, who were asked to score the designed camouflage schemes using the evaluation system proposed. The data from simulation assessments and individual evaluations show that the computer-aided simulation assessments conducted as part of this research can efficiently and objectively evaluate the camouflage effect on military objects.
Rocznik
Strony
39--50
Opis fizyczny
Bibliogr. 33 poz., rys., tab.
Twórcy
autor
  • Army Engineering University of PLA, College of Field Engineering, Haifu Lane No.1, Qinhuai district, Nanjing, Jiangsu 210007, China
autor
  • Army Engineering University of PLA, College of Field Engineering, Haifu Lane No.1, Qinhuai district, Nanjing, Jiangsu 210007, China
autor
  • Unit 32381 of PLA, Beijing 10071, China
autor
  • Army Engineering University of PLA, College of Field Engineering, Haifu Lane No.1, Qinhuai district, Nanjing, Jiangsu 210007, China
autor
  • Army Engineering University of PLA, College of Field Engineering, Haifu Lane No.1, Qinhuai district, Nanjing, Jiangsu 210007, China
autor
  • Army Engineering University of PLA, College of Field Engineering, Haifu Lane No.1, Qinhuai district, Nanjing, Jiangsu 210007, China
autor
  • Army Engineering University of PLA, College of Field Engineering, Haifu Lane No.1, Qinhuai district, Nanjing, Jiangsu 210007, China
Bibliografia
  • 1. Cuthill I C, Stevens M, Sheppard J, Maddocks T, Párraga C A, Troscianko T S (2005) Disruptive coloration and background pattern matching. Nature, 434(3): 72-74.
  • 2. Merilaita S, Lind J (2005) Backgroundmatching and disruptive coloration, and the evolution of cryptic coloration. Proc. R. Soc. B, 272(5): 665-670.
  • 3. Todd P A (2009) Testing for camouflage using virtual prey and human ‘predators’. Journal of Biological Education, 43(2): 81-84.
  • 4. Miyazawa S. (2020) Pattern blending enriches the diversity of animal colorations. Science Advances 6 (49) DOI: 10.1126/sciadv.abb9107.
  • 5. Marshall, Messenger (1996) Colour-blind camouflage. Nature, 382(6): 408-409.
  • 6. Chiao C C, Emma J K, Roger T H (2005) Disruptive body patterning of cuttlefish (Sepia officinalis) requires visual information regarding edges and contrast of objects in natural substrate backgrounds. Biol. Bull, 208(7): 7-11.
  • 7. Mathger L M, Barbosa A, Miner S, Hanlon R T (2006) Color blindness and contrast perception in cuttlefish (Sepia officinalis) determined by a visual sensorimotor assay. Vision Research, 46(5): 1746-1753.
  • 8. Xue F, Wu F, Wang J W, Hu Y (2018) Camouflage texture design based on its camouflage performance evaluation. Neurocomputing, 274: 106-114.
  • 9. Singha S K, Dhawaleb C A, Misrac S (2013) Survey of Object Detection Methods in Camouflaged Image, Ieri Procedia, 4:351-357.
  • 10. Lin C J, Chang C C, Liu B S (2014) Developing and Evaluating a Target-Background Similarity Metric for Camouflage Detection, PLoS One, 9(2): e87310.
  • 11. Cho W J, Kim M, Lee E, Kim S, Han J, Han K H (2015) Camouflage Assessment of Color Pattern Strategies in Different Environmental Contexts, HCI 2015 Posters, Part 1 CCIS 528: 170-173.
  • 12. Maddalena L, Petrosino A (2019) Selforganizing background subtraction using color and depth data. Multimedia Tools and Applications, 78(9): 11927-11948.
  • 13. Raman R, Choudhury S K, Bakshi S (2018) Spatiotemporal optical blob reconstruction for object detection in grayscale videos. Multimedia Tools and Applications, 77(1): 741-762.
  • 14. Yao H, Liu X, Tang Z, Qin C, Tian Y (2019) Adaptive image camouflage using human visual system model. Multimedia Tools and Applications, 78(7): 8311-8334.
  • 15. Juarez-Sandoval O U, Cedillo-Hernandez M, Nakano-Miyatake M, Cedillo-Hernandez A (2018) Digital image ownership authentication via camouflaged unseen-visible watermarking. Multimedia Tools and Applications, 77(20): 26601-26634.
  • 16. Yang X, Xu W D, Jia Q, Liu J (2020) MF-CFI: a fused evaluation index for camouflage patterns based on human visual perception. Defence Technology, https://doi.org/10.1016/j.dt.2020.08.007
  • 17. Liu Z Y, Ding F, Xu Y, Han X (2020) Background dominant colors extraction method based on color image quick fuzzy c-means clustering algorithm. Defence Technology, https://doi.org/10.1016/j.dt.2020.10.002
  • 18. Gretzmaeher F M, Ruppert G S, Nyberg S (1998) Camouflage assessment considering human perception data. Proc. of SPIE, 3375: 58-67.
  • 19. Meitzler T J, Kistner R W, Pibil W T, Sohn E, Bryk D, Bednarz D (1998) Computing the probability of target detection in dynamic visual scenes containing clutter using fuzzy logical approach. Optical Engineering, 37(7): 1951-1959.
  • 20. Thomas M, Markus M (2007) Computeraided camouflage assessment in real-time. Proc. of SPIE, 6543: 654307-654307-11.
  • 21. Thomas M, Thomas H, Markus M (2009) CART III: Improved camouflage assessment using moving target indication. Proc. of SPIE, 7300: 73000N-73000N-11.
  • 22. Wong I, Meitzler T, Sohn E, Lane K (2006) Computer estimated probability of detection: can you hide from a computer? ADA454643.
  • 23. Meitzler T J, Bednarz D, Bryk D, Lane K, Sohn E (2003) Use of a photo simulation Laboratory for estimating vehicle detection probability. Optical Engineering, 42(6): 1820-1825.
  • 24. Hogervorst M A, Toet A, Jacobs P (2010) Design and evaluation of (urban) camouflage. Proc. of SPIE, 7662: 766205-766205-11.
  • 25. Friškovec M et al. (2010) Design and Evaluation of a camouflage pattern for the Slovenian urban environment. Journal of Imaging Science and Technology, 54(2): https://doi.org/10.2352/J.IMAGINGSCI.TECHNOL.2010.54.2.020507
  • 26. Hepfinger L, Stewardson C, Rock K, Lesher L L, Kramer F M, Mcintosh S, Patterson J, Isherwood K, Rogers G, Nguyen H (2010) Soldier camouflage for operation enduring freedom (OEF): pattern-in-picture (PIP) technique for expedient human-in-the-loop camouflage assessment, ADA532947.
  • 27. Xin Yang, Wei-dong Xu, Qi Jia, Ling Li, Wan-nan Zhu, Ji-yao Tian, Hao Xu (2020) Research on extraction and reproduction of deformation camouflage spot based on generative adversarial network model. Defence Technology, 16(3): 555-563.
  • 28. Hall J R, Matthews O, Volonakis T N, Liggins E, Lymer K P, Baddeley R, Cuthill I C, Scott-Samuel N E (2020) A platform for initial testing of multiple camouflage patterns. Defence Technology, https://doi.org/10.1016/j.dt.2020.11.004
  • 29. Information on http: //www.xrite.cn, 2023-03-28.
  • 30. Luo M R, Cui G, Rigg B (2001) The Development of the CIE 2000 Colour-Difference Formula: CIEDE2000. Color Research and Application, 26(5): 340-350.
  • 31. Luo M R (2002) The CIE 2000 colour difference formula: CIEDE2000. SPIE, 4421: 554-559.
  • 32. Jia Q, Lv X L, Zeng Z Y, Xu W D (2011) Application of Descriptor in Evaluation of Target Camouflage Effectiveness, Journal of Applied Sciences, 29(5): 483-486.
  • 33. Jia Q, Xu W D, Hu J H, Liu J, Yang X, Zhu L Y (2020) Design and evaluation of digital camouflage pattern by spot combination, Multimedia tools and applications, 79(29-30): 22047-22064.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b874d4d1-4e15-49fc-af7f-a48896d10870
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