Tank segmentation of infrared images with complex background for the homing anti-tank missile

Zhou, Yulong; Gao, Min; Fang, Dan; Zhang, Baoquan

doi:10.1016/j.infrared.2016.06.008

Cited by 5 publications

(1 citation statement)

References 17 publications

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“…The other method uses optical imaging principles to identify the object area and filter out some background pixels. Conventional image thresholding is then applied to the rest of the histogram [7]. Shannon entropy and Tsallis entropy are measured in background class and object class, respectively, and the smaller one is selected at each intensity [8]; this is to improve the accuracy even in longrange correlation.…”

Section: Previous Workmentioning

confidence: 99%

Double Thresholding with Sine Entropy for Thermal Image Segmentation

Manda¹,

Hyun²

2021

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Traditional thresholding methods are often used for image segmentation of real images. However, due to distinct characteristics of infrared thermal images, it is difficult to ensure an optimal image segmentation using the traditional thresholding algorithms, and therefore, sometimes this can lead to over-segmentation, missing object information, and/or spurious responses in the output. To overcome these issues, we propose a new thresholding technique that makes use of the sine entropy-based criterion. Moreover, we build a double thresholding technique that makes use of two thresholds to get the final image thresholding result. Besides, we introduce the sine entropy concept as a supplement of the Shannon entropy in creating threshold-dependent criterion derived from the grayscale histogram. We found that the sine entropy is more robust in interpreting the strength of the long-range correlation in the gray levels compared to the Shannon entropy. We have experimented with our method on several infrared thermal images collected from standard image databases to describe the performance. On comparing with the state-of-art methods, the qualitative results from the experiments show that the proposed method achieves the best performance with an average sensitivity of 0.98 and an average misclassification error of 0.01, and second-best performance with an average sensitivity of 0.99 and an average specificity of 0.93.

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Section: Previous Workmentioning

confidence: 99%

Double Thresholding with Sine Entropy for Thermal Image Segmentation

Manda¹,

Hyun²

2021

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Robust noise hybrid active contour model for infrared image segmentation using orientation column filters

Zhang,

Qian,

Wan

et al. 2023

Journal of Modern Optics

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Optically transparent infrared selective emitter for visible-infrared compatible camouflage

Luo

et al. 2022

Opt. Express

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Visible-infrared compatible camouflage is significant to enhance the equipment survivability through counteracting the modern detecting and surveillance systems. However, there are still great challenges in simultaneously achieving multispectral camouflage with high transmittance in visible, low emissivity in the atmospheric windows and high emissivity in the non-atmospheric window, which can be attributed to the mutual influence and restriction within these characteristics. Here, we proposed an optically transparent infrared selective emitter (OTISE) composed of three Ag-ZnO-Ag disk sub-cells with anti-reflection layers, which can synchronously improve the visible transmittance and widen absorption bandwidth in the non-atmospheric window by enhancing and merging resonance response of multi-resonators. Test results reveal that low emissivity in infrared atmospheric windows, high emissivity in the 5-8 µm non-atmospheric window and high optical transparency have been obtained. In addition, the radiative flux of OTISE in 3-5 µm and 8-14 µm are respectively 34.2% and 9.3% of that of blackbody and the energy dissipation of OTISE is 117% of that of chromium film. Meanwhile, it keeps good optical transparency due to the ultrathin Ag film. This work provides a novel strategy to design the optically transparent selective emissive materials, implying a promising application potential in visible and infrared camouflage technology.

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Tank segmentation of infrared images with complex background for the homing anti-tank missile

Cited by 5 publications

References 17 publications

Double Thresholding with Sine Entropy for Thermal Image Segmentation

Double Thresholding with Sine Entropy for Thermal Image Segmentation

Robust noise hybrid active contour model for infrared image segmentation using orientation column filters

Optically transparent infrared selective emitter for visible-infrared compatible camouflage

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