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Automatic image analysis process for the detection of concealed weapons

机译:用于隐藏武器检测的自动图像分析过程

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The goal of this research is to develop a process, using current imaging hardware and without human intervention, that provides an accurate and timely detection alert of a concealed weapon and its location in the image of the luggage. There are several processes in existence that are able to highlight or otherwise outline a concealed weapon in baggage but so far those processes still require a highly trained operator to observe the resulting image and draw the correct conclusions. We attempted three different approaches in this project. The first approach uses edge detection combined with pattern matching to determine the existence of a concealed pistol. Rather than use the whole body of the weapon which varies significantly, the trigger guard was used since it is fairly consistent in dimensions. While the processes were reliable in detecting a pistol's presence, on any but the simplest of images, the computational time was excessive and a substantial number of false positives were generated. The second approach employed Daubechie wavelet transforms but the results have so far been inconclusive. A third approach involving an algorithm based on the scale invariant feature transform (SIFT) is proposed.
机译:这项研究的目的是开发一种使用当前成像硬件且无需人工干预的过程,该过程可为隐藏武器及其在行李箱图像中的位置提供准确,及时的检测警报。存在几种能够突出显示或以其他方式勾勒出行李中隐藏武器的过程,但到目前为止,这些过程仍需要训练有素的操作员来观察所得图像并得出正确的结论。在该项目中,我们尝试了三种不同的方法。第一种方法使用边缘检测与模式匹配相结合来确定隐藏的手枪的存在。不是使用武器的整体变化很大的东西,而是使用了扳机护板,因为它的尺寸相当一致。尽管该过程可以可靠地检测出手枪的存在,但在除最简单的图像之外的任何图像上,计算时间都过长,并且会生成大量的误报。第二种方法采用了Daubechie小波变换,但结果至今尚无定论。提出了第三种方法,该方法涉及基于尺度不变特征变换(SIFT)的算法。

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