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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >A symbol spotting approach in graphical documents by hashing serialized graphs
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A symbol spotting approach in graphical documents by hashing serialized graphs

机译:通过散列序列化图形在图形文档中发现符号的方法

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摘要

In this paper we propose a symbol spotting technique in graphical documents. Graphs are used to represent the documents and a (sub)graph matching technique is used to detect the symbols in them. We propose a graph serialization to reduce the usual computational complexity of graph matching. Serialization of graphs is performed by computing acyclic graph paths between each pair of connected nodes. Graph paths are one-dimensional structures of graphs which are less expensive in terms of computation. At the same time they enable robust localization even in the presence of noise and distortion. Indexing in large graph databases involves a computational burden as well. We propose a graph factorization approach to tackle this problem. Factorization is intended to create a unified indexed structure over the database of graphical documents. Once graph paths are extracted, the entire database of graphical documents is indexed in hash tables by locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. We have performed detailed experiments with various datasets of line drawings and compared our method with the state-of-the-art works. The results demonstrate the effectiveness and efficiency of our technique.
机译:在本文中,我们提出了图形文档中的符号点技术。图形用于表示文档,而(子)图形匹配技术用于检测文档中的符号。我们提出一种图形序列化方法,以降低图形匹配的通常计算复杂度。图的序列化是通过计算每对连接的节点之间的非循环图路径来执行的。图路径是图的一维结构,在计算方面较便宜。同时,即使在存在噪声和失真的情况下,它们也可以实现可靠的定位。大图数据库中的索引也涉及计算负担。我们提出了一种图形分解方法来解决这个问题。分解旨在在图形文档数据库上创建统一的索引结构。提取图形路径后,将通过路径形状描述符的位置敏感哈希(LSH)在哈希表中为整个图形文档数据库建立索引。散列数据结构旨在在亚线性时间内执行近似k-NN搜索。我们对各种线描数据集进行了详细的实验,并将我们的方法与最新技术进行了比较。结果证明了我们技术的有效性和效率。

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