{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:20:37Z","timestamp":1732040437901},"reference-count":54,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T00:00:00Z","timestamp":1619481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"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\u20131000 nm range). The proposed method is based on the visualization of heme-components bands in the 500\u2013700 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 \u00d7 512 \u00d7 224, in which 1000 \u00d7 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.<\/jats:p>","DOI":"10.3390\/s21093045","type":"journal-article","created":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T10:19:11Z","timestamp":1619518751000},"page":"3045","source":"Crossref","is-referenced-by-count":30,"title":["Hyperspectral Imaging for Bloodstain Identification"],"prefix":"10.3390","volume":"21","author":[{"given":"Maheen","family":"Zulfiqar","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan 64200, Pakistan"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3320-2261","authenticated-orcid":false,"given":"Muhammad","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Chiniot-Faisalabad Campus, Chiniot 35400, Pakistan"},{"name":"Dipartimento di Matematica e Informatica-MIFT, University of Messina, 98121 Messina, Italy"}]},{"given":"Ahmed","family":"Sohaib","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan 64200, Pakistan"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3860-4948","authenticated-orcid":false,"given":"Manuel","family":"Mazzara","sequence":"additional","affiliation":[{"name":"Institute of Software Development and Engineering, Innopolis University, 420500 Innopolis, Russia"}]},{"given":"Salvatore","family":"Distefano","sequence":"additional","affiliation":[{"name":"Dipartimento di Matematica e Informatica-MIFT, University of Messina, 98121 Messina, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ksi\u0105\u017cek, K., Romaszewski, M., G\u0142omb, P., Grabowski, B., and Cholewa, M. 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