automatic image analysis process for the detection of concealed weapons
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.
edge detection pattern matching daubechies wavelets scale invariant feature transform invariants weapons detection