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首页> 外文期刊>International journal of computer vision and iImage processing >Scale Space Co-Occurrence HOG Features for Word Spotting in Handwritten Document Images
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Scale Space Co-Occurrence HOG Features for Word Spotting in Handwritten Document Images

机译:用于手写文档图像中单词发现的比例空间共现HOG功能

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摘要

>In this paper, the authors proposed a Scale Space Co-occurrence Histograms of Oriented Gradients method (SS Co-HOG) for retrieving words from digitized handwritten documents. The poor performance of HOG based word spotting in handwritten documents is due to that HOG ignores spatial information of neighboring pixels whereas Co-HOG captures the spatial information of neighboring pixels through counting the occurrence of the gradient orientations of two or more neighboring pixels. The authors employed three scale parameter representation of an image and at each scale, they divide the word image into blocks and Co-HOG features are extracted from each block and finally concatenate them into form a feature descriptor. The proposed method is evaluated using precision and recall metrics through experimentation conducted on popular datasets such as IAM and GW and confirmed that their method outperforms for both the datasets.
机译: >在本文中,作者提出了一种“方向梯度的尺度空间共现直方图”(SS Co-HOG),用于从数字化手写文档中检索单词。手写文档中基于HOG的单词斑点的性能较差是由于HOG忽略了相邻像素的空间信息,而Co-HOG通过计算两个或更多相邻像素的梯度方向的出现来捕获相邻像素的空间信息。作者采用图像的三个比例参数表示,并在每个比例下将单词图像划分为块,并从每个块中提取Co-HOG特征,最后将它们连接起来形成特征描述符。通过对IAM和GW等流行数据集进行实验,使用精密度和召回率指标对提出的方法进行了评估,并证实了它们的方法在这两个数据集上均表现优异。

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