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Use of adaptive segmentation in handwritten phrase recognition

机译:自适应分段在手写短语识别中的使用

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摘要

Research in handwriting recognition has thus far been primarily focused on recognizing words and phrases. In fact, phrases are usually treated as a concatenation of the constituent words making it in essence an enhanced word recognizer. In this paper we present a methodology that will take advantage of the spacing between the words in a phrase to aid the recognition process. The novelty of our approach lies in the fact that the determination of word breaks is made in a manner that adapts to the writing style of the individual. The parameters that decide whether a particular gap between components is an inter-word gap or an inter-character gap are computed without the necessity of generalizing over a large training set. Rather, it is tuned to the distribution of the gaps within the instance of the phrase image being examined. We compare our approach to the methods described in the literature that simply ignore the significance of gaps in a phrase. Our experiments show an improvement of about 5% in recognition rates. On a test set of about 1400 phrase images the segmentation method "misses" only 2% of the true word break points. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 19]
机译:迄今为止,手写识别的研究主要集中于识别单词和短语。实际上,短语通常被视为组成单词的串联,从本质上讲使它成为增强的单词识别器。在本文中,我们提出了一种方法,该方法将利用短语中单词之间的间隔来辅助识别过程。我们的方法的新颖性在于,断字的确定以适合个人写作风格的方式进行。计算决定组件之间的特定间隙是单词间间隙还是字符间间隙的参数,而无需对大型训练集进行概括。而是将其调整为要检查的短语图像实例中的间隙分布。我们将我们的方法与文献中描述的方法进行了比较,这些方法只是忽略了短语中空格的重要性。我们的实验表明识别率提高了约5%。在约1400个词组图像的测试集上,分割方法仅“错过”了真实断词点的2%。 (C)2001模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:19]

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