摘要
本研究旨在提出手印显现选择性的量化方法,并讨论手印显现选择性的影响因素。首先利用Image J软件得到手印图像的灰度曲线,再利用Origin软件对灰度曲线进行分析,最终得到手印显现选择性的定量计算方法,即灰度曲线的波峰(对应乳突纹线)与波谷(对应小犁沟)积分的比值。本研究通过502熏染显现法、氨基黑10B显现法对量化方法进行了验证,结果表明该量化方法可行,此外,从显现试剂与客体性质两方面分析了影响手印显现选择性的主要因素。通过该研究,为手印显现效果的量化特别是选择性的定量评估提供了有益的参考。
This work aims to propose a quantitative method for calculating the selectivity in latent fingerprint development,and discuss the effect factors of the developing selectivity.Firstly,the gray value curve of developed fingerprint image was obtained from Image J software.The gray value curve was then analyzed by means of Origin software.The developing selectivity was ultimately derived by the ratio of integrated peaks(friction ridges)to integrated valleys(furrows)in gray value curve.This method was tested and verified to be feasible through the super glue fuming method and Amino black 10B method.In addition,the effects of developing reagents and substrate properties on the fingerprint developing selectivity were investigated.This work provides beneficial references for quantitative evaluating the result especially the selectivity of latent fingerprint development.
作者
于海峰
沈敦璞
鞠金晟
王猛
YU Haifeng;SHEN Dunpu;JU Jinsheng;WANG Meng(Department of Trace Examination,National Police University of China,Shenyang 110035,Liaoning,P.R.China;Key Laboratory of Impression Evidence Examination and Identification Technology,Ministry of Public Security,Shenyang 110035,Liaoning,P.R.China)
出处
《影像科学与光化学》
CAS
2019年第6期507-514,共8页
Imaging Science and Photochemistry
基金
国家自然科学基金青年基金项目(21205139、21802169)
公安部科技强警基础工作专项项目(2014GABJC033、2018GABJC07、2018GABJC09)
辽宁省高等学校优秀人才支持计划(LJQ2014130)
辽宁省高等学校创新人才支持计划(LR2017055)
中国刑事警察学院研究生创新能力提升项目(2018YCYB29、2018YCYB33)资助
关键词
潜在手印
手印显现
选择性
量化
latent fingerprint
fingerprint development
selectivity
quantification