Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby c...Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.展开更多
This paper reports an alternative approach to the evaluation of infrared camouflage effectiveness via a multi-fractal method. By calculating multi-fractal spectra of the target region and the background regions in an ...This paper reports an alternative approach to the evaluation of infrared camouflage effectiveness via a multi-fractal method. By calculating multi-fractal spectra of the target region and the background regions in an infrared image, the spectrum shape features and the discrete Frechet distances among these spectra were used to analyze the camouflage effectiveness of the target qualitatively and quantitatively,and the correlation coefficients of the spectra were further used as the index of camouflage effectiveness.It was found that the camouflaged target had better camouflage effectiveness than the target without camouflage in the same one background, and the same one camouflaged target had different camouflage effectiveness in different backgrounds. On the whole, the target matching well with its background had high camouflage effectiveness value. This approach can expand the application of multi-fractal theory in infrared camouflage technology, which should be useful for the research of infrared camouflage materials, the design of camouflage patterns as well as the deployment of military equipment in battlefield.展开更多
基金sponsored by the National Defense Science and Technology Key Laboratory Fund(Grant No.61422062205)the Equipment Pre-Research Fund(Grant No.JCKYS2022LD9)。
文摘Brain functional networks model the brain's ability to exchange information across different regions,aiding in the understanding of the cognitive process of human visual attention during target searching,thereby contributing to the advancement of camouflage evaluation.In this study,images with various camouflage effects were presented to observers to generate electroencephalography(EEG)signals,which were then used to construct a brain functional network.The topological parameters of the network were subsequently extracted and input into a machine learning model for training.The results indicate that most of the classifiers achieved accuracy rates exceeding 70%.Specifically,the Logistic algorithm achieved an accuracy of 81.67%.Therefore,it is possible to predict target camouflage effectiveness with high accuracy without the need to calculate discovery probability.The proposed method fully considers the aspects of human visual and cognitive processes,overcomes the subjectivity of human interpretation,and achieves stable and reliable accuracy.
基金supported by the State Key Laboratory of Pulsed Power Laser Technology, College of Electronic Engineering, National University of Defense Technology, Hefei, China。
文摘This paper reports an alternative approach to the evaluation of infrared camouflage effectiveness via a multi-fractal method. By calculating multi-fractal spectra of the target region and the background regions in an infrared image, the spectrum shape features and the discrete Frechet distances among these spectra were used to analyze the camouflage effectiveness of the target qualitatively and quantitatively,and the correlation coefficients of the spectra were further used as the index of camouflage effectiveness.It was found that the camouflaged target had better camouflage effectiveness than the target without camouflage in the same one background, and the same one camouflaged target had different camouflage effectiveness in different backgrounds. On the whole, the target matching well with its background had high camouflage effectiveness value. This approach can expand the application of multi-fractal theory in infrared camouflage technology, which should be useful for the research of infrared camouflage materials, the design of camouflage patterns as well as the deployment of military equipment in battlefield.
