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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Providing order to the handwritten TLS task: A complexity index
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Providing order to the handwritten TLS task: A complexity index

机译:向手写TLS任务提供订单:复杂性指数

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摘要

Text Line Segmentation (TLS) methods are intended to locate and separate text lines in document images for different stages of image analysis such as word spotting, keyword search, text alignment, text recognition and other stages of indexation involved in the retrieval of information from handwritten documents. The design of the proposed methods for the TLS and the tuning of their parameters assume a level of complexity according to the language and the writing style of a document collection. Therefore, the performance of these methods is not maintained against documents of greater or lesser complexity. In this paper, we present TLS-ICI, a TLS Intrinsic Complexity Index that allows measuring the complexity of a document for the TLS task, without the necessity of a human gold standard. Through experimentation, we demonstrate how our proposed TLS-ICI provides an order to both the TLS methods and the image-based handwritten documents. In this way, with our proposed complexity index it is possible to select the most appropriated method for each document of a collection, reducing the time spent in exhaustive tests and increasing the performance. In addition, we demonstrate through a new hybrid TLS method that the TLS-ICI outperforms previous individual TLS methods. The dataset consists of several standard TLS collections of contemporary and ancient texts from different languages and alphabets such as English, Spanish, Arabic, and Chinese, Greek, Khmer, Persian, Bengali, Oriya, Kannada and Nahuatl.
机译:文本线段(TLS)方法旨在在文档图像中定位和单独的文本行,以获取不同阶段的图像分析,例如Word Spotting,关键字搜索,文本对齐,文本识别和从手写的信息检索中涉及的其他阶段文件。根据文档集合的语言和写入样式,TLS的提出方法和参数的调整的设计的设计假设复杂程度。因此,这些方法的性能不受更大或更少复杂性的文件。在本文中,我们提出了TLS-ICI,TLS内在复杂性指数,允许测量TLS任务的文档的复杂性,而无需人为金标准。通过实验,我们展示了我们所提出的TLS-ICI如何为TLS方法和基于图像的手写文件提供订单。通过这种方式,通过我们提出的复杂性指数,可以选择集合的每个文档的最拨款方法,从而减少了在详尽测试中花费的时间并提高了性能。此外,我们通过一种新的混合TLS方法来证明TLS-ICI优于先前的单个TLS方法。该数据集包括来自不同语言和字母的多种标准TLS集合,例如英语,西班牙语,阿拉伯语和中文,希腊语,高棉,波斯语,孟加拉,奥里雅,kannada和Nahuatl等不同语言和字母。

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