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Fuzzy c-means clustering based digital camouflage pattern design and its evaluation

机译:基于模糊的C型群体基于数码伪装模式设计及其评价

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Optical camouflage is one of the significant ways to protect military weapons in modern wars. Effective camouflage design can largely reduce the conspicuity of the fixed targets in a real battlefield. In this paper, an innovative digital camouflage pattern design based on fuzzy c-means clustering and its evaluation is presented to imitate the background both in color and texture. In this new method, histogram quantization and matching between the real background and I military standard colors is first carried out in HSV color space. Then camouflage pattern is abstained by a combination of the fuzzy c-means clustering and morphological operations, such as open operation and close operation. And the camouflage scene is composed with tank using new digital camouflage pattern. Finally, several common edge detectors are utilized to give an objective evaluation to the new digital camouflage pattern which is painting on the target in a composed camouflage scene. Assessment results also show the effectiveness and potency of the new proposed method.
机译:光学伪装是保护军事武器在现代战争中的重要方法之一。有效的伪装设计可以大大减少真正的战场上的固定目标的阴谋。本文介绍了一种基于模糊C型聚类的创新数字伪装模式设计及其评估,以模仿颜色和纹理。在这种新方法中,首先在HSV颜色空间中进行直方图量化和匹配。然后,通过模糊C-Means聚类和形态操作的组合弃置伪装图案,例如开放操作和关闭操作。并且伪装场景由坦克使用新的数字伪装模式组成。最后,利用了几个公共边缘探测器对新的数字伪装图案进行客观评估,这是在组合的伪装场景中绘制的新数字伪装模式。评估结果还表明了新的方法的有效性和效力。

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