Supervised segmentation of textures in backscatter images

P. Paclík, R. Duin, Geert M. P. van Kempen, R. Kohlus
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引用次数: 19

Abstract

In this paper we present an application of statistical pattern recognition for segmentation of backscatter images (BSE) in product analysis of laundry detergents. Currently, application experts segment BSE images interactively which is both time consuming and expert dependent. We present a new, automatic procedure for supervised BSE segmentation which is trained using additional multi-spectral EDX images. Each time a new feature selection procedure is employed to find a convenient feature subset for a particular segmentation problem. The performance of the presented algorithm is evaluated using ground-truth segmentation results. It is compared with that of interactive segmentation performed by the analyst.
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后向散射图像纹理的监督分割
本文提出了一种基于统计模式识别的后向散射图像分割(BSE)在洗衣粉产品分析中的应用。目前,应用专家对疯牛病图像进行交互式分割既耗时又依赖于专家。我们提出了一种新的自动过程,用于监督BSE分割,该过程使用额外的多光谱EDX图像进行训练。每次都使用一个新的特征选择过程来为特定的分割问题找到一个方便的特征子集。利用真值分割结果对该算法的性能进行了评价。将其与分析人员进行的交互式分割进行了比较。
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