BACKGROUND & AIMS:
:Banknotes are often found in high-profile crimes such as armed robberies, bribery, and terrorist activity. However, such exhibits present a challenge to forensic operatives regarding fingermarks development, due to their mass quantities, potential for fingermarks on both sides, and their unique complex background in terms of color, irregular patterns, and topography. Hence, the standard development protocols become inefficient, due to the difficulty in achieving high contrast images over the background. This study focused on finding an operational sequence that would minimize the time of work on polymer banknotes, in terms of both development and image processing. Thirty-two fingermarks were developed by vacuum metal deposition (VMD), black magnetic powder, and cyanoacrylate fuming (CA) followed by visualization and imaging by reflected short-wave UV (RUVIS) (96 in total), showing a distinct advantage to the CA and RUVIS imaging over the other two techniques with a 75% success rate in the dark and high background regions, due to its physical principle which neutralizes high background interference. The images were then scanned by the automatic fingerprint identification system (AFIS) to test its ability to correctly differentiate false background features from real ones, again, showing a superiority of the RUVIS with 63% of the total initial marked features, being real. Overall, the CA and RUVIS sequence was found to be an ultimate method for multiple, same-type surfaces, with the RUVIS capable of visualization and capturing of the images simultaneously, significantly reducing the time of development and image processing.
背景与目标:
: 纸币经常出现在武装抢劫、贿赂、恐怖活动等备受瞩目的犯罪中。然而,由于指纹的数量,两侧的指纹潜力以及在颜色,不规则图案和地形方面独特的复杂背景,此类展品对法医人员的指纹开发提出了挑战。因此,由于难以在背景上获得高对比度图像,因此标准开发协议变得效率低下。这项研究的重点是找到一种操作顺序,该顺序可以在显影和图像处理方面最大程度地减少聚合物钞票的工作时间。通过真空金属沉积 (VMD),黑色磁粉和氰基丙烯酸酯发烟 (CA),然后通过反射短波UV (RUVIS) 进行可视化和成像 (总共96),开发了32个指纹。由于其抵消高背景干扰的物理原理,显示出CA和RUVIS成像相对于其他两种技术的明显优势,在黑暗和高背景区域具有75% 的成功率。然后由自动指纹识别系统 (AFIS) 扫描图像,以测试其正确区分虚假背景特征与真实背景特征的能力,再次显示出RUVIS的优越性,其中63% 的全部初始标记特征是真实的。总体而言,发现CA和RUVIS序列是用于多个相同类型表面的最终方法,RUVIS能够同时可视化和捕获图像,从而显着减少了显影和图像处理的时间。