Feature Extraction and Selection in Archaeological Images for Automatic Annotation

M. Salah, Ameni Yengui, M. Neji
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引用次数: 1

Abstract

In this paper, we present two steps in the process of automatic annotation in archeological images. These steps are feature extraction and feature selection. We focus our research on archeological images which are very much studied in our days. It presents the most important steps in the process of automatic annotation in an image. Feature extraction techniques are applied to get the feature that will be used in classifying and recognizing the images. Also, the selection of characteristics reduces the number of unattractive characteristics. However, we reviewed various images of feature extraction techniques to analyze the archaeological images. Each feature represents one or more feature descriptors in the archeological images. We focus on the descriptor shape of the archaeological objects extraction in the images using contour method-based shape recognition of the monuments. So, the feature selection stage serves to acquire the most interesting characteristics to improve the accuracy of the classification. In the feature selection section, we present a comparative study between feature selection techniques. Then we give our proposal of application of methods of selection of the characteristics of the archaeological images. Finally, we calculate the performance of two steps already mentioned: the extraction of characteristics and the selection of characteristics.
面向自动标注的考古图像特征提取与选择
本文介绍了考古图像自动标注的两个步骤。这两个步骤分别是特征提取和特征选择。我们的研究重点是考古图像,这些图像在我们的时代被研究得非常多。介绍了图像自动标注过程中最重要的步骤。特征提取技术用于提取图像分类和识别所需的特征。此外,特征的选择减少了不吸引人的特征的数量。然而,我们回顾了各种图像特征提取技术来分析考古图像。每个特征代表考古图像中的一个或多个特征描述符。利用基于轮廓法的古迹形状识别方法,重点研究了图像中考古物体的描述符形状提取。因此,特征选择阶段是为了获取最有趣的特征,以提高分类的准确性。在特征选择部分,我们对特征选择技术进行了比较研究。在此基础上,提出了考古图像特征选择方法的应用建议。最后,我们计算了特征提取和特征选择两个步骤的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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