论文标题
使用K均值聚类的高光谱文档图像中的伪造检测
Forgery Detection in a Questioned Hyperspectral Document Image using K-means Clustering
论文作者
论文摘要
高光谱成像允许根据成像传感器的光谱分辨率分析数百个光谱带中的图像。高光谱文档图像是由高光谱摄像机捕获的，因此可以根据其独特的光谱特征在不同的频段中观察到文档。为了在文档中检测伪造，基于高光谱成像的各种墨水不匹配检测技术在区分视觉上相似的油墨方面具有巨大的潜力。不同材料的油墨即使具有相同的颜色，它们也会显示出不同的光谱特征。文档图像的高光谱分析可以识别和歧视视觉上相似的墨水。基于此分析，法医可以识别文档的真实性。在本文中，提出了广泛的墨水不匹配检测技术，该技术使用Kmean聚类根据其独特的光谱响应来识别不同的墨水，并将它们分为不同的簇。
Hyperspectral imaging allows for analysis of images in several hundred of spectral bands depending on the spectral resolution of the imaging sensor. Hyperspectral document image is the one which has been captured by a hyperspectral camera so that the document can be observed in the different bands on the basis of their unique spectral signatures. To detect the forgery in a document various Ink mismatch detection techniques based on hyperspectral imaging have presented vast potential in differentiating visually similar inks. Inks of different materials exhibit different spectral signature even if they have the same color. Hyperspectral analysis of document images allows identification and discrimination of visually similar inks. Based on this analysis forensic experts can identify the authenticity of the document. In this paper an extensive ink mismatch detection technique is presented which uses KMean Clustering to identify different inks on the basis of their unique spectral response and separates them into different clusters.
