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Discrimination of human and animal bloodstains using hyperspectral imaging
Subtitle: Specim IQ (Specim, Spectral Imaging Ltd., Oulu, Finland)
Metadata
| Additional title | Subtitle: Specim IQ (Specim, Spectral Imaging Ltd., Oulu, Finland) | |
| Person(s) who is (are) responsible for the content of the research data | Babian, Carsten - Institute for Legal Medicine, Leipzig University (ORCID: 0000-0002-6621-9705) | |
| Person(s) who is (are) responsible for the content of the research data | Cooney, Gary Sean - Innovation Center Computer Assisted Surgery (ICCAS) | |
| Person(s) who is (are) responsible for the content of the research data | Chalopin, Claire - Innovation Center Computer Assisted Surgery (ICCAS) | |
| Person(s) who is (are) responsible for the content of the research data | Köhler, Hannes - Innovation Center Computer Assisted Surgery (ICCAS) (ORCID: 0000-0001-9342-3288) | |
| Description of further data processing | A support vector machine (SVM) binary classifier was trained for the discrimination of bloodstains of human (n = 20) and five animal species: pig (n = 20), mouse (n = 16), rat (n = 5), rabbit (n = 5), and cow (n = 20). On an independent test set, the SVM model achieved accuracy, precision, sensitivity, and specificity values of 96, 97, 95, and 96%, respectively. Segmented images of bloodstains aged over a period of two months were produced, allowing for the clear visualisation of the discrimination of human and animal bloodstains. | |
| Type of data acquisition | Observation: Spectral imaging | |
| Used research instruments or devices | Specim IQ ® (Specim, Spectral Imaging Ltd., Oulu, Finland) | |
| Research objects | Substance: human and animal blood | |
| Abstract | To address the question of blood origin, the novel application of visible-near infrared hyperspectral imaging (HSI) is used for the detection and discrimination of human and animal bloodstains. The HSI system used is a portable, non-contact, non-destructive method for the determination of blood origin. A support vector machine (SVM) binary classifier was trained for the discrimination of bloodstains of human (n = 20) and five animal species: pig (n = 20), mouse (n = 16), rat (n = 5), rabbit (n = 5), and cow (n = 20). | |
| Applied methods and techniques | Hyperspectral imaging and chemometric methods | |
| Additional descriptive information to understand the data | Data and methods are described in detail in the attached documents and in https://doi.org/10.1007/s12024-023-00689-0. | |
| Counties, the data is referencing | GERMANY | de |
| Additional keywords | Animal blood · Hyperspectral imaging (HSI) · Support vector machine (SVM) · Neighbourhood component feature selection (NCFS) · Forensics | |
| Language | eng | |
| Year or period of data production | 2020-2021 | |
| Publication year | 2024 | |
| Publisher | Universität Leipzig | |
| References on related materials | IsPartOf: 123456789/6055 (Handle) | |
| Content of the research data | Text, Image, Dataset, Software: Text, Image, Dataset: Master Thesis, Journal publication, Measurements | |
| Holder of usage rights | Universität Leipzig | |
| Usage rights of the data | CC-BY-4.0 | |
| Additional precise description of discipline | Forensic Science | |
| Discipline(s) | Chemistry | de |
| Discipline(s) | Engineering | de |
| Discipline(s) | Medicine | de |
| Title of the dataset | Discrimination of human and animal bloodstains using hyperspectral imaging |
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Measurements [1]
Spectral measurements performed by G. S. Cooney (2020-2021)