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Structural feature-based evaluation method of binarization techniques for word retrieval in the degraded Arabic document images

机译:基于结构特征的二值化技术在退化阿拉伯文档图像中检索词的评估方法

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摘要

One of the most important and necessary steps in the process of document analysis and recognition is the binarization, which allows extracting the foreground from the background. Several binarization techniques have been proposed in the literature, but none of them was reliable for all image types. This makes the selection of one method to apply in a given application very difficult. Thus, performance evaluation of binarization algorithms becomes therefore vital. In this paper, we are interested in the evaluation of binarization techniques for the purpose of retrieving words from the images of degraded Arabic documents. A new evaluation methodology is proposed. The proposed evaluation methodology is based on the comparison of the visual features extracted from the binarized document images with ground truth features instead of comparing images between themselves. The most appropriate thresholding method for each image is the one for which the visual features of the identified words in the image are "closer" to the features of the reference words. The proposed technique was used here to assess the performances of eleven algorithms based on different approaches on a collection of real and synthetic images.
机译:二值化是文档分析和识别过程中最重要和必要的步骤之一,它可以从背景中提取前景。文献中已经提出了几种二值化技术,但是它们都不对所有图像类型都可靠。这使得很难选择一种方法来应用于给定的应用程序。因此,二值化算法的性能评估因此变得至关重要。在本文中,我们对二值化技术的评估感兴趣,目的是从退化的阿拉伯文档的图像中检索单词。提出了一种新的评估方法。所提出的评估方法基于对从二值化文档图像中提取的视觉特征与地面真实特征进行比较,而不是对它们之间的图像进行比较。对于每个图像,最合适的阈值处理方法是使图像中已识别单词的视觉特征“更接近”参考单词的特征。在此使用所提出的技术来评估基于真实图像和合成图像集合上不同方法的十一种算法的性能。

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