基于光谱双向反射分布函数的纤维物证鉴别

Fiber Evidence Identification Based on Spectral Bidirectional Reflectance Distribution Function

根据Locard的交换理论,纤维证据可以帮助重建犯罪事件。通常,纤维物证的鉴定采用的是化学成分分析方法,但该方法会破坏物证的完整性。本文基于光谱双向反射分布函数(BRDF)理论,建立了相关测试和分析方法,以解决纤维物证留存的长效性。针对三组纤维样品(每组包含6种同色不同材质的纤维样品)建立分析案例的方法,采用一阶微分和差分法提取光谱特征,分析光谱BRDF数据;依据光谱曲线提取拟合函数和残差系数,进行差异化比较;然后在物理机制上通过建立Davis模型模拟光谱BRDF曲线,实现了案例中的物证与可疑结果的有效判定。实验结果为纤维物证特征的鉴别提供了一种有效且无损的探测技术和分析方法,对刑侦分析和嫌疑人定罪具有重要意义。

According to Locard's switching theory,fiber evidence can help reconstruct criminal incidents.Generally,fiber evidence is identified by chemical composition analysis;however,the integrity of material evidence will be destroyed.For this reason,we established a testing and analysis method based on the theory of bidirectional reflectance distribution function(BRDF)to ensure the long-term retention of fiber evidence.To be specific,three groups of fiber samples were selected,with each group containing six kinds of fiber samples with the same color and different materials.The first-order differential and difference methods were used to extract spectral characteristics and analyze spectral BRDF.According to spectral curve fitting,the fitting function and residual coefficient were extracted for differential comparison.From the physical mechanism,a Davis model was built to simulate the spectral BRDF curve.As a result,the material evidence and suspicious results in the cases were effectively determined.The experimental results provide an effective and non-destructive detection technology and analysis method for the identification of fiber evidence characteristics,which greatly facilitates criminal investigation analysis and conviction.