Blood is the key evidence for forensic investigation because it carries critical information to help reconstruct the crime scene, confirm or exclude a suspect, and analyze the timing of a crime. Conventional bloodstain detection uses chemical methods. Those methods require cautious sample preparations. They are destructive to samples in principle. Some of them are carcinogenic to investigators. They require experienced investigators and constrained conditions. Spectral imaging methods are an emerging technique for bloodstain detection in forensic science. It provides a non-destructive, non-contact, non-toxic, and real-time methodology for presumptive bloodstain searching, either in the field or in the laboratory.
This thesis prototyped two crime scene bloodstain detection imaging systems. The first generation crime scene imaging system is a LCTF based visible hyperspectral imaging system. Detection results of a simulated indoor crime scene show that bloodstains can be highlighted. However, this system has some drawbacks. First of all, it only records spectral information at 400 nm to 700 nm spectral range. Bloodstains on some substrates may not be detected. Second, it has a low SNR. This is mainly due to the low transmittance of the LCTF. Third, its FOV is only $pm$7 degrees from normal. Fourth, it cannot work continuously for a long time. The lighting module is attached next to the camera, which emits excessive heat and warms the camera quickly. Fifth, it is not calibrated into physical units such as radiance or reflectance. Therefore, a second generation crime scene imaging system was developed.
The second generation crime scene imaging system is a VNIR multispectral imaging system. It uses interference filters to construct the spectral bands. Blood reflectance spectral features were extracted from the comparison of blood and visually similar non-blood substances on various common found substrates. Three spectral features were used to construct the VNIR spectral bands of the multispectral imaging system. A linear regression pixel-wise model was used to enhance the spatial uniformity of the CMOS sensor. The lens falloff was corrected. The transmittance spectra of interference filters with various incident angles were calibrated. The system was calibrated to reflectance with the required 10\% accuracy from first principle based modeling.
Two verification tests were carried using the MSI system. The first test is a systematic test where 9 substrates were laid radially symmetric to study the spectral shift effect introduced by the interference filters. Comparing with the reflectance error, the spectral shift is found to be not as influential for bloodstain detection using RBD, RX, and TAD methods. The result from the first principle based modeling agrees with the test. The second test is a semi-realistic indoor crime scene test where different sizes of blood spatters were directly applied to off-white carpet, dark carpet, door, and painted wall under various daytime environmental conditions. The image processing workflow includes noise reduction, bloodstain detection, and data fusion. Bloodstains were detected in a large FoV in the semi-realistic crime scene on most substrates, except for a small spatter on dark color thick carpet. SNR is the major factor impacting the detectability, the 2nd major factor is the extra visible lighting which lacks of near infrared information.
The contribution of this work are three aspects: the first is the developing and prototyping an interference filter based multispectral imaging system used at a large FoV for forensic bloodstain detection. The second is the discussion of the spectral shift impact compared with the reflectance calibration error suggests that spectral shift is not as influential as reflectance calibration error. Third, the discussion of the impact of environmental conditions towards bloodstain detection on this MSI system.
利用这个多光谱系统进行了两次验证性实验。第一次实验是个系统性检测。实验时，为研究干涉滤光片的光谱位移现象，9种基质呈对称辐射状分布于场景中。与反射率标定误差相比，光谱位移在利用RBD, RX, 和TAD的方法来检测血迹的实验中并没有影响太大。基于第一原理的模型与实验结果相吻合。第二项检测是一项半真实性室内犯罪场景实验，在不同的白天光照条件下，在近乎白色的地毯、暗色地毯、门上、和漆墙上都施用了不同大小的血迹。图像处理过程包括去噪，血迹检测，和数据融合。结果，除了在暗色厚地毯上的一个小血迹没有检测出来，这个半真实性实验在相对很大的视场和多数基质上都检测到了血迹。分析认为信噪比是影响检测效果的主要原因，其次是缺少近红外信息的光照条件。
Imaging Science (Ph.D.)
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Yang, Jie, "Crime Scene Blood Evidence Detection Using Spectral Imaging" (2019). Thesis. Rochester Institute of Technology. Accessed from
RIT – Main Campus