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Camouflage texture evaluation using a saliency map

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Abstract

Camouflage effect evaluation and examination is an important procedure in digital camouflage pattern design as it is helpful in improving the objectivity and effectiveness thereof. Based on the human vision mechanism, we propose a new method, which creates a saliency map of the input image that can quantitatively evaluate the degree to which the target and surrounding background differ with respect to color brightness and space distribution. Then, we use this saliency map to evaluate the effect of camouflage design. Experimental results demonstrate that the saliency map is an effective approach for evaluating camouflage design.

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References

  1. Xu, W., Lv, X., Chen, B., Xue, S.: A model based on texture analysis for the performance evaluation of camouflage screen equipment [J]. Acta Armamentarium 23(3), 329–331 (2002)

    Google Scholar 

  2. Hu, J., Zhu, C., Wang, Y., Lu, J.: A method for detection and evaluation on pattern painting camouflage effect. China Meas. Technol. 33(2), 67–69 (2007)

    Google Scholar 

  3. Huang, Y., Wu, W., Gong, Y., Chen, L.: A new method of edge camouflage evaluation based on the gray polymerization histogram. Opt. Technol. 37(5), 601–606 (2011)

    Google Scholar 

  4. Lin, W., Chen, Y., Gao, H., Lin, L., Wang, J.: A method of camouflage evaluation based on texture analysis model of Gabor wavelet. Acta Armamentarium 28(10), 1191–1194 (2007)

    Google Scholar 

  5. Zhu, H., Du, S.: Camouflage assessment based on wavelet texture characteristics. Comput. Eng. 34(16), 227–229 (2008)

    Google Scholar 

  6. Jia, Q., Lü, X., Zeng, Z., Xu, W.: Application of descriptor in evaluation of Target camouflage effectiveness. J. Appl. Sci. 29(5), 483–486 (2011)

    Google Scholar 

  7. Luo, S.: The perception computing of visual information [M]. Science Press, Beijing (2010)

    Google Scholar 

  8. Sang, N., Li, Z., Zhang, T.: Applications of human visual attention mechanisms in object detection [J]. Infrared Laser Eng. 33(1), 38–42 (2004)

    Google Scholar 

  9. Itti, L., Koch, C.: Computational modeling of visual attention [J]. Nat. Rev. Neurosci. 2(3), 194–230 (2001)

    Article  Google Scholar 

  10. Itti, L., Koch, C.: Feature combination strategies for saliency-based visual attention systems [J]. J. Electron. Imaging 10(1), 161–169 (2001)

    Article  Google Scholar 

  11. Itti, L., Koch, C., Niebur, E.A.: Model of saliency-based visual attention for rapid scene analysis [J]. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254–1259 (1998)

    Article  Google Scholar 

  12. Swain, M.J., Ballard, D.H.: Color indexing. Int. J. Comput. Vis. 17(1), 11–32 (1991)

    Article  Google Scholar 

  13. Cheng, M., Zhang, G., Niloy, J.M.: Global contrast based salient region detection. Proc. Comput. Vis. Pattern Recognit. pp. 409–416 (2012)

  14. Tamura, H., Mori, S., Yamawaki, T.: Textural features corresponding to visual perception [J]. IEEE Trans. Syst. Man Cybern. 8(6), 460–473 (1978)

    Article  Google Scholar 

  15. Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary pattern [J]. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002)

    Article  Google Scholar 

  16. Zhai, Y., Shah, M.: Visual attention detection in video sequences using spatiotemporal cues. ACM Multimed. pp. 815–824 (2006)

  17. Satoh, S., Miyake, S.: A model of overt visual attention based on scale-space theory [J]. Syst. Comput. Jpn. 35(10), 1–13 (2004)

    Article  Google Scholar 

  18. Gretzmacher, F.M., Ruppert, G.S., Nyberg, S.: Camouflage assessment considering human perception data [J]. Proc. SPIE 3375, 58–67 (1998)

    Article  Google Scholar 

Download references

Acknowledgments

This research is supported by the National Natural Science Foundation of China (No. 61202283) and the Open Project of State Key Laboratory of Virtual Reality Technology and Systems of China (No. BUAA-VR-10KF-5).

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Correspondence to Xue Feng.

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Feng, X., Guoying, C., Richang, H. et al. Camouflage texture evaluation using a saliency map. Multimedia Systems 21, 169–175 (2015). https://doi.org/10.1007/s00530-014-0368-y

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