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CLASSIFICATION AND RECOGNITION OF TOMB INFORMATION IN HYPERSPECTRAL IMAGE

机译:高光谱图像中的古墓信息分类与识别

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There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.
机译:古墓中有大量具有重要历史信息的材料。但是,在许多情况下,人眼或真彩色相机可能会掩盖这些物质并使它们变得难以区分。为了有效地对古墓中的物质进行分类鉴定,将高光谱成像技术应用于山西古墓的考古研究中。首先,通过主成分分析(PCA)变换选择古墓底部包括主要信息的特征带,以实现数据维度。然后,使用支持向量机(SVM)基于特征带进行图像分类。最后,通过光谱分析和光谱匹配来识别古墓底部的材料。结果表明,基于特征带的支持向量机不仅可以保证分类的准确性,而且可以缩短数据处理时间,提高分类效率。在材料识别中,发现在可见光中识别出的同一物质实际上是两种不同的物质。该研究结果为考古工作提供了新的参考和研究思路。

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