主管:中华人民共和国司法部
主办:司法鉴定科学研究院
ISSN 1671-2072  CN 31-1863/N

中国司法鉴定 ›› 2021 ›› Issue (5): 75-81.DOI: 10.3969/j.issn.1671-2072.2021.05.008

• 鉴定综述 • 上一篇    下一篇

常见微量物证的颜色分析

胡 灿,朱 军,梅宏成,郭洪玲,郑继利,李亚军   

  1. 公安部物证鉴定中心,北京 100038

  • 收稿日期:2020-01-16 出版日期:2021-09-30 发布日期:2021-10-21
  • 作者简介:胡灿(1988—),女,副研究员,博士,主要从事理化检验分析。E-mail:hucanjiayou@126.com
  • 基金资助:
    中央级公益性科研院所基本科研业务费专项资金项目(2018JB015)。

Color Analysis of Common Trace Evidence

HU Can, ZHU Jun, MEI Hongcheng, GUO Hongling, ZHENG Jili, LI Yajun   

  1. Institute of Forensic Science of China, Beijing 100038, China

  • Received:2020-01-16 Published:2021-09-30 Online:2021-10-21

摘要: 颜色是泥土、纤维、油漆等常见微量物证的重要特征之一,颜色分析是实现物证准确鉴定的重要内容。然而目前国内法庭科学领域物证颜色分析还主要依赖于肉眼观察及主观描述,不利于颜色这一重要特征作为科学证据在庭审过程中使用。通过对常用的RGB颜色模型、孟塞尔颜色模型和Lab颜色模型的特点介绍,并对影响泥土、纤维、油漆物证颜色的因素进行归纳,以明确物证颜色差异产生的原因。然后对常用的目测法、光谱法、机器视觉法等颜色分析方法的特点与应用情况进行了总结,对颜色分析未来的工作方向提出建议,以期为国内从事微量物证检验研究的同行提供参考。

关键词:

微量物证, 颜色分析, 光谱法, 机器视觉法

Abstract: Color is one of the important characteristics of trace physical evidence such as soil, fiber and paint, and color analysis is an important content in achieving accurate identification of physical evidence. However, the color analysis of physical evidence in the field of forensic science in China is still largely dependent on visual observation and subjective description, which is not conducive to the use of color as scientific evidence in the trial. By introducing the characteristics of RGB color model, Munsell color model, and Lab color model, and by summarising the factors that affect the color of soil, fiber and paint, this paper identifies the causes of colour variation in evidence. The paper then summarises the characteristics and applications of commonly used colour analysis methods such as visual inspection, spectrum method and machine vision method, and puts forward corresponding suggestions for the future work direction of color analysis, with a view to providing a reference for colleagues engaged in the study of trace physical evidence in China.

Key words:

trace material evidence, color analysis, spectroscopy, machine vision method

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