ArticleSensors (Basel, Switzerland)2021
Hyperspectral Imaging for Bloodstain Identification.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Tanshinone Content Prediction and Geographical Origin Classification ofFoods (Basel, Switzerland) · 2024Article
- Identification of different blood concentration of domestic cat (Open veterinary journal · 2024Article
- Discrimination of human and animal bloodstains using hyperspectral imaging.Forensic science, medicine, and pathology · 2024Article
- Correction of Substrate Spectral Distortion in Hyper-Spectral Imaging by Neural Network for Blood Stain Characterization.Sensors (Basel, Switzerland) · 2022Article
- On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime.Genes · 2021Review
- Recent Advances in Multi- and Hyperspectral Image Analysis.Sensors (Basel, Switzerland) · 2021Article
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Authors and funding
5 authors.
Funding
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Abstract
Blood is key evidence to reconstruct crime scenes in forensic sciences. Blood identification can help to confirm a suspect, and for that reason, several chemical methods are used to reconstruct the crime scene however, these methods can affect subsequent DNA analysis. Therefore, this study presents a non-destructive method for bloodstain identification using Hyperspectral Imaging (HSI, 397-1000 nm range). The proposed method is based on the visualization of heme-components bands in the 500-700 nm spectral range. For experimental and validation purposes, a total of 225 blood (different donors) and non-blood (protein-based ketchup, rust acrylic paint, red acrylic paint, brown acrylic paint, red nail polish, rust nail polish, fake blood, and red ink) samples (HSI cubes, each cube is of size 1000 × 512 × 224, in which 1000 × 512 are the spatial dimensions and 224 spectral bands) were deposited on three substrates (white cotton fabric, white tile, and PVC wall sheet). The samples are imaged for up to three days to include aging. Savitzky Golay filtering has been used to highlight the subtle bands of all samples, particularly the aged ones. Based on the derivative spectrum, important spectral bands were selected to train five different classifiers (SVM, ANN, KNN, Random Forest, and Decision Tree). The comparative analysis reveals that the proposed method outperformed several state-of-the-art methods.
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