Exposure fusion for concealed weapon detection

Ekta M. Upadhyay, N. Rana
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引用次数: 16

Abstract

In recent years there has been a need to improvise the security of the general public as well as the safety of public assets like airports and buildings for which, the biggest hurdle is detection of weapons concealed underneath a person's clothing. It is desirable sometimes to be able to detect concealed weapons from a standoff distance, especially when it is impossible to arrange the flow of people through a controlled procedure. Therefore, we propose a novel algorithm to generate one multi exposed - multi modal image from a set of visual images with multiple exposures and a set of infrared images with multiple exposures. The method employs homomorphic filter, entropy of blocks and blending approach for image fusion. Experiments were performed on different sets of multi exposed images by varying the block size and the blending parameter which shows that the proposed method outperforms the results obtained without homomorphic filter.
用于隐蔽武器探测的暴露融合
近年来,有必要对普通公众的安全以及机场和建筑物等公共资产的安全进行临时防范,其中最大的障碍是检测隐藏在人衣服下面的武器。有时,能够在距离很远的地方发现隐藏的武器是可取的,特别是在不可能通过控制程序安排人员流动的情况下。因此,我们提出了一种新的算法,从一组具有多次曝光的视觉图像和一组具有多次曝光的红外图像中生成一幅多曝光的多模态图像。该方法采用同态滤波、块熵和混合方法进行图像融合。通过改变块大小和混合参数,在不同的多曝光图像集上进行了实验,结果表明,该方法优于无同态滤波的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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