01423nas a2200157   4500000000100000008004100001100002400042700002300066700002100089700002000110245006900130856003700199490000800236520100700244022001401251       2021                            d1 aMichał Romaszewski1 aPrzemysław Głomb1 aArkadiusz Sochan1 aMichał Cholewa00aA dataset for evaluating blood detection in hyperspectral images  uhttps://arxiv.org/abs/2008.102540 v3203 a<p>The sensitivity of imaging spectroscopy to haemoglobin derivatives makes it a promising tool for detecting blood. However, due to complexity and high dimensionality of hyperspectral images, the development of hyperspectral blood detection algorithms is challenging. To facilitate their development, we present a new hyperspectral blood detection dataset. This dataset, published under an open access license, consists of multiple detection scenarios with varying levels of complexity. It allows to test the performance of Machine Learning methods in relation to different acquisition environments, types of background, age of blood and presence of other blood-like substances. We have explored the dataset with blood detection experiments, for which we have used a hyperspectral target detection algorithm based on the well-known Matched Filter detector. Our results and their discussion highlight the challenges of blood detection in hyperspectral data and form a reference for further works.</p>
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