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New feature extraction method for classification of agricultural products from x-ray images

机译：基于x射线图像的农产品分类新特征提取方法

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Abstract: Classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non- invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items. This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discrimination between damaged and clean items. This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work the MRDF is applied to standard features. The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC data. !23
机译：摘要：讨论了随机取向的开心果坚果的实时X射线图像分类。最终目标是开发一种系统，用于自动非侵入式检测传送带上的有缺陷产品。我们将讨论新功能的提取，以便更好地区分损坏的物品和干净的物品。特征提取和分类阶段是本文的新内容。我们新的最大代表性以及对损坏和干净物品的区分。特征提取和分类阶段是本文的新内容。我们的新的最大表示和判别特征（MRDF）提取方法可计算非线性特征，这些非线性特征将用作新修改的k最近邻分类器的输入。在这项工作中，MRDF被应用于标准功能。 MRDF对输入类别的各种概率分布具有鲁棒性，并显示出可以提供良好的分类和新的ROC数据。 ！23

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