Keyword Spotting in Handwritten Documents Using Projections of Oriented Gradients

George Retsinas, G. Louloudis, N. Stamatopoulos, B. Gatos
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引用次数: 20

Abstract

In this paper, we present a novel approach for segmentation-based handwritten keyword spotting. The proposed approach relies upon the extraction of a simple yet efficient descriptor which is based on projections of oriented gradients. To this end, a global and a local word image descriptors, together with their combination, are proposed. Retrieval is performed using to the euclidean distance between the descriptors of a query image and the segmented word images. The proposed methods have been evaluated on the dataset of the ICFHR 2014 Competition on handwritten keyword spotting. Experimental results prove the efficiency of the proposed methods compared to several state-of-the-art techniques.
利用定向梯度投影在手写文档中识别关键字
本文提出了一种基于分词的手写关键字识别方法。提出的方法依赖于提取一个简单而有效的描述符,该描述符基于定向梯度的投影。为此,提出了一种全局和局部词图像描述符及其组合。检索使用查询图像的描述符和分割的词图像之间的欧氏距离。所提出的方法已经在ICFHR 2014手写体关键词识别大赛的数据集上进行了评估。实验结果证明了该方法与几种最新技术相比的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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