图文并茂的背景对自动评估指痕质量的影响。

Bérénice Bonnaz, Andy Bécue
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引用次数: 0

摘要

在指痕检测领域,背景插图可能会对指痕的可见度产生负面影响。它们确实会在局部降低对比度或掩盖脊纹细节。在开展研究项目时,选择素色还是有插图的基底主要取决于研究目标以及所研究技术的发展水平(例如,新试剂、两种技术之间的比较、半操作测试)。此外,目前还不清楚负责对检测到的指痕质量进行分级的人工评估员究竟是如何处理站在背景指纹上的指痕的。在最近的出版物中,潜伏指纹质量度量(LQM)和改进潜伏指纹质量度量(ILFQM)算法被认为是传统人工评估的潜在替代方法。因此,本研究的作者希望评估这些算法在图解背景下的性能。为了实现这一目标,480 个指痕被放置在多孔(240 个)和非多孔(240 个)的物品上,这些物品呈现出各种类型的插图(如彩色区域、文字、几何图形、线条)。然后依次使用了几种检测技术:对于多孔物品,采用 1,2-茚二酮/锌+茚三酮+物理显影剂;对于无孔物品,则采用超强粘合剂熏蒸后染色或黑色磁粉。共获得 884 张图片,并通过 LQM 和 ILFQM 对其质量进行了评估。然后对结果进行分析,以确定背景指纹是否会影响这两种算法提供的指标,如果会,影响程度如何。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impact of illustrated backgrounds on the automatic assessment of fingermark quality.

In the fingermark detection field, background illustrations may negatively impact the visibility of the marks in presence. They can indeed locally reduce the contrast or mask ridge details. When conducting a research project, the choice for plain or illustrated substrates is mostly driven by the research objectives as well as the development level of the investigated technique (e.g., new reagent, comparison between two techniques, semi-operational test). Also, it is not clear how the human assessors in charge of grading the quality of the detected fingermarks actually cope with fingermarks standing astride background prints. In recent publications, latent quality metrics (LQM) and improved latent fingerprint quality metrics (ILFQM) algorithms have been identified as potential alternatives to traditional human assessment. The authors of the present study were therefore interested in assessing the performance of these algorithms with regards to illustrated backgrounds. To reach that goal, 480 fingermarks were deposited on porous (240) and non-porous (240) items presenting various kinds of illustrations (e.g., colored areas, writings, geometric shapes, lines). Several detection techniques were then applied in sequence: 1,2-indanedione/zinc + ninhydrin + physical developer for porous items, and superglue fuming followed by dye-staining or black magnetic powder for non-porous items. A total of 884 pictures were obtained and their quality assessed by LQM and ILFQM. The results were then analyzed to determine if background prints may influence the metrics provided both algorithms, and if yes, to which extent.

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