Keyword-detection approach to automatic image annotation

V. Viitanierni, Jorma T. Laaksonen
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引用次数: 20

Abstract

In this paper we consider the problem of automatically annotating images with keywords. We first discuss performance measures for the problem in some length. We propose a new information-theory based measure de-symmetrised mutual information (DTMI). We then describe a straightforward solution to the annotation problem. We first train a set of classifiers to detect the presence of each individual keyword in the set of training images. For this we use the PicSOM image analysis framework. We then describe a method of converting the classifier outputs back into keyword annotations for the test set. We compare the performance of the proposed method experimentally to that of other methods presented in the literature. For the experiments we use data from the Corel database. The result of the comparison is favourable to the proposed method.
基于关键词检测的图像自动标注方法
本文研究了用关键词对图像进行自动标注的问题。我们首先用一定篇幅讨论这个问题的性能度量。提出了一种新的基于信息论的测度去对称互信息(DTMI)方法。然后,我们描述了注释问题的一个直接解决方案。我们首先训练一组分类器来检测训练图像集中每个关键字的存在。为此,我们使用PicSOM图像分析框架。然后,我们描述了一种将分类器输出转换回测试集的关键字注释的方法。我们将所提出的方法的性能与文献中提出的其他方法进行了实验比较。对于实验,我们使用来自Corel数据库的数据。对比结果表明,所提出的方法是有效的。
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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