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Developing and Evaluating a Target-Background Similarity Metric for Camouflage Detection

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  • Chiuhsiang Joe Lin
  • Chi-Chan Chang
  • Bor-Shong Liu

Abstract

Background: Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. Methodology: In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. Significance: The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

Suggested Citation

  • Chiuhsiang Joe Lin & Chi-Chan Chang & Bor-Shong Liu, 2014. "Developing and Evaluating a Target-Background Similarity Metric for Camouflage Detection," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
  • Handle: RePEc:plo:pone00:0087310
    DOI: 10.1371/journal.pone.0087310
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    Cited by:

    1. Anna E Hughes & Emmanuelle S Briolat & Lina MarĂ­a Arenas & Eric Liggins & Martin Stevens, 2023. "Varying benefits of generalist and specialist camouflage in two versus four background environments," Behavioral Ecology, International Society for Behavioral Ecology, vol. 34(3), pages 426-436.

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