基于分形和粗糙集理论的烟幕干扰舰船检测

Zhiguo Li, Xiaoke Yan, Yudong Bai
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引用次数: 0

摘要

在红外图像中,同类自然景物在统计上是自相似的,即它们的分形维数基本保持不变。然而,在边缘处,维数被低估了,因为边缘向表面添加了一个确定性成分,而这一成分在计算分形维数时并没有被假设。因此,“分形”的局部程度被用来区分感兴趣区域(ROI)与杂波背景。然后,基于粗糙集不可分辨关系理论对舰船进行检测,并根据舰船的几何特征进行识别;在基于TMS320C6416的图像跟踪器上进行了实验,结果表明该方法具有良好的自动识别精度和计算效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Warship detection in smoke screen interference based on fractal and rough set theory
In IR images, the same kind of natural scenes are self-similarity statistically, namely their fractal dimension remains unchanged approximately. At edges, however, the dimension is underestimated, because edges add a deterministic component to the surface which is not assumed to be presented for the purpose of calculation of the fractal dimension. Thus, the local degree of ‘fractality’ is used to differentiate the regions-of-interest (ROI) from the clutter background. Then, the warship is detected based on indiscemibility relation of Rough sets (RS) theory and is recognized based on the geometric characters of warship. Experiments on the image tracker based on TMS320C6416 were conducted, and the results demonstrated that the approach performs well in automatic recognition accuracy and computational efficiency.
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