A robust firearm identification algorithm of forensic ballistics specimens

Z L Chuan, A A Jemain, C-Y Liong, N A M Ghani, L K Tan
2017 Journal of Physics, Conference Series  
Applications of surface metrology in firearm identification X Zheng, J Soons, T V Vorburger et al. -Topography measurements for determining the decay factors in surface replication J Song, P Rubert, A Zheng et al. -Development of ballistics identification--from image comparison to topography measurement in surface metrology J Song, W Chu, T V Vorburger et al. -This content was downloaded from IP address 103.53.34.12 on 30/11 Abstract. There are several inherent difficulties in the existing
more » ... n the existing firearm identification algorithms, include requiring the physical interpretation and time consuming. Therefore, the aim of this study is to propose a robust algorithm for a firearm identification based on extracting a set of informative features from the segmented region of interest (ROI) using the simulated noisy center-firing pin impression images. The proposed algorithm comprises Laplacian sharpening filter, clustering-based threshold selection, unweighted least square estimator, and segment a square ROI from the noisy images. A total of 250 simulated noisy images collected from five different pistols of the same make, model and caliber are used to evaluate the robustness of the proposed algorithm. This study found that the proposed algorithm is able to perform the identical task on the noisy images with noise levels as high as 70%, while maintaining a firearm identification accuracy rate of over 90%.
doi:10.1088/1742-6596/890/1/012126 fatcat:kos7xb4ljbft7etjlpixc6nktq