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Math Spotting: Retrieving Math in Technical Documents Using Handwritten Query Images

机译:数学点:使用手写查询图像检索技术文档中的数学

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A method for locating mathematical expressions in document images without the use of optical character recognition is presented. An index of document regions is produced from recursive X-Y trees produced for each page in the corpus. Queries are provided as images of handwritten expressions, for which an X-Y tree is computed. During retrieval, the query is looked up in the document region index using features of its X-Y tree, producing a set of candidate regions. Candidate regions are ranked by the similarity of vertical pixel projections in their upper and lower halves with those of the query image, as computed using Dynamic Time Warping of the image columns. In an experiment, ten participants each wrote twenty queries from a 200-page corpus. On average, the top-10 retrieval candidates included a candidate covering 43.3% of the test query image (σ = 14.0), with the correct page being returned between 30.0% and 85.0% of the time across participants (μ = 63.2%, s = 14.9%). When testing using the original query images, 90.0% of the queries were retrieved correctly.
机译:提出了一种在不使用光学字符识别的情况下在文档图像中定位数学表达式的方法。文档区域的索引是从为语料库中的每个页面生成的递归X-Y树生成的。提供查询作为手写表达的图像,并为其计算X-Y树。在检索期间,查询使用其X-Y树的功能在文档区域索引中查找,从而生成一组候选区域。候选区域按其上下半部分的垂直像素投影与查询图像的相似度进行排序,这是使用图像列的动态时间扭曲来计算的。在一个实验中,十个参与者各自从一个200页的语料库中写了二十个查询。平均而言,排名前10位的检索候选者包括覆盖43.3%的测试查询图像的候选者(σ= 14.0),正确的页面在参与者中的返回时间介于30.0%到85.0%之间(μ= 63.2%,s = 14.9%)。使用原始查询图像进行测试时,正确检索了90.0%的查询。

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