清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Automated ‘lights-out’ searching of all recovered fingerprints: Review of the current workflow for latent fingerprint processing in Queensland, Australia

指纹(计算) 工作流程 计算机科学 匹配(统计) 过程(计算) 指纹验证比赛 指纹识别 数据挖掘 人工智能 数据库 医学 病理 操作系统
作者
Troy O’Malley,Matt N. Krosch,Paul Peacock,Rechelle Cook,David H. Neville
出处
期刊:Forensic Science International [Elsevier BV]
卷期号:337: 111372-111372 被引量:3
标识
DOI:10.1016/j.forsciint.2022.111372
摘要

The process of linking an offender to a crime scene via their fingerprints has historically required significant human effort to compare latent fingerprints recovered from the scene with known fingerprints of a suspect. Increasing the speed of such comparisons, whilst maintaining accuracy and reliability and minimising error, is crucial for providing rapid intelligence to police investigators. One major opportunity for streamlining fingerprint examination is the adaptation of 'lights-out' technology to the comparison and matching of latent fingerprints. Here, we review the development, trial and validation process undertaken by the Queensland Police Service (QPS), Australia, to support implementation of a lights-out latent (LOL) workflow for automated latent fingerprint searching that is fully integrated with the existing case management systems. Targeted trials were undertaken using random selections of previously identified latent fingerprints that were searched using the LOL workflow against a local 10-print database. The results suggested that the LOL workflow could identify up to 44% of latent fingerprints with minimal human intervention and supported its implementation for all latent fingerprint comparisons in QPS casework. Review of LOL casework comparison outcomes for 2019 revealed that LOL-based identifications contributed approximately one quarter of all fingerprint identifications. Several procedural and technical factors that influenced the speed and efficiency of the LOL workflow are discussed, along with opportunities for improvement and future validation as an expert system.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
kd1412完成签到 ,获得积分10
21秒前
Kao应助科研通管家采纳,获得10
26秒前
猪肉超人菜婴蚊完成签到,获得积分10
34秒前
RONG完成签到 ,获得积分10
39秒前
1分钟前
BOBO发布了新的文献求助20
1分钟前
云峤完成签到 ,获得积分10
1分钟前
planA完成签到,获得积分10
1分钟前
wjlxw完成签到,获得积分20
1分钟前
科研通AI6.2应助jasonwee采纳,获得10
2分钟前
cadcae完成签到,获得积分10
2分钟前
面汤完成签到 ,获得积分10
2分钟前
小蘑菇应助BOBO采纳,获得10
2分钟前
nkr完成签到,获得积分10
2分钟前
Kao应助科研通管家采纳,获得10
2分钟前
Kao应助科研通管家采纳,获得10
2分钟前
Kao应助科研通管家采纳,获得10
2分钟前
Kao应助科研通管家采纳,获得10
2分钟前
灵宝宝完成签到,获得积分10
2分钟前
六一儿童节完成签到 ,获得积分0
2分钟前
奇博士完成签到,获得积分10
2分钟前
美好时光完成签到 ,获得积分10
3分钟前
3分钟前
jasonwee发布了新的文献求助10
3分钟前
3分钟前
super旵发布了新的文献求助10
3分钟前
superspace完成签到 ,获得积分10
3分钟前
moodlunatic完成签到,获得积分10
3分钟前
Hao完成签到,获得积分0
3分钟前
Copyright应助moodlunatic采纳,获得10
3分钟前
sci完成签到 ,获得积分10
4分钟前
Kao应助科研通管家采纳,获得10
4分钟前
Kao应助科研通管家采纳,获得10
4分钟前
4分钟前
super旵完成签到,获得积分10
4分钟前
富贵发布了新的文献求助10
4分钟前
xiaoyi完成签到 ,获得积分10
4分钟前
831143完成签到 ,获得积分0
4分钟前
林好人完成签到 ,获得积分10
4分钟前
wood完成签到,获得积分10
4分钟前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Gründe der Seele:Die Wiener Psychatrie im 20.Jahrhundert 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
Organic Reactions, Volume 116 1000
Current concepts in cutaneous toxicity : proceedings of the Fourth Conference on Cutaneous Toxicity, Washington, D.C., May 9-11, 1979 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7269988
求助须知:如何正确求助?哪些是违规求助? 8890469
关于积分的说明 18793316
捐赠科研通 6945424
什么是DOI,文献DOI怎么找? 3203699
关于科研通互助平台的介绍 2376553
邀请新用户注册赠送积分活动 2179581