摘要
目的提出一种基于Python平台的校正方法,解决曲面客体上指纹在采用光学方法提取后发生变形的问题。方法根据标尺刻度的变化,自适应地求得最佳匹配曲面以及任意一点的放大率,通过逆变换消除曲面客体造成的畸变。结果使用该方法校正曲率半径固定的简单曲面上指纹,结果的平均误差为5.3%,使用HGXJ-360曲面物证图像展平系统校正结果的平均误差为7%。使用该方法校正曲率半径变化的复杂曲面上的指纹,亦能取得显著的校正效果。结论本文提出的渐变曲率曲面指纹的自适应校正方法能够自动化地校正各种曲面客体上的指纹,在简单曲面客体上其效果优于现有的成熟的校正方法,在复杂曲面客体上亦能得到优异的效果,能够为现场勘查中各类曲面物体上指纹的无损提取提供有力辅助。
Objective A Python-based self-adaptive correction was to propose for fingerprints that had been extracted from the surfaces of gradual curvature so that the difficult problem could be solved about identifying the deformed fingerprints after optical development and visualization on curving objects.Methods A calibration-engraved scaling ruler was used to measure the curvature surface where fingerprint was deposited.Based on the measurement and calculation of the deformation from the ruler’s calibration,a correction approach was set up through Python3.4 programming plus devisal so that both the optimal matching surface and magnification rate were to figure out adaptively,making the distortion eliminated with reverse transformation.Therefore,a revision can be carried out into bringing the fingerprint to proximity to its original pattern.Results The fingerprints on simple curving radius-fixed surfaces have been able to correct with obvious effect under the average error of 5.3%,contrasting to the 7% from HGXJ-360,the Curvature-surface Physical Evidence Image Flattening System developed by Evidential Materials Authentication Center of Shanghai Public Security Bureau.For the fingerprints on complex surfaces of changing curvature radii,significant correction effects have even been attained furthermore.Conclusion The correction approach established here can automatically revise the fingerprints on various curved surfaces towards proximity to their original patterns,demonstrating effective for fingerprints on both the simple radius-fixed curvature surfaces and complex radius-changing ones,therefore capable of providing strong supports with nondestructive extraction of fingerprints on various surfaces in crime scene investigation.
作者
栗赫遥
高畅
蔡能斌
包清
LI Heyao;GAO Chang;CAI Nengbin;BAO Qing(Shanghai Police College,Shanghai 200137,China;Criminal Investigation Department of Shanghai Public Security Bureau,Shanghai 200083,China;University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《刑事技术》
2021年第4期342-348,共7页
Forensic Science and Technology
基金
“十三五”国家重点研发计划(2017YFC0803806)。
关键词
曲面客体
复杂曲面
指纹校正
curved object
complex curved surface
fingerprint correction
作者简介
第一作者:栗赫遥,女,辽宁葫芦岛人,硕士,讲师,研究方向为公安学及犯罪学。E-mail:li-heyao@163.com;通信作者:包清,男,上海人,博士研究生,高级工程师,研究方向为物证技术学及模式识别。E-mail:2459083965@qq.com。
