{"title":"A Method for Machine-Readable Zones Location Based on a Combination of the Hough Transform and the Search for Feature Points","authors":"B. Savelyev, N. Skoryukina, V. Arlazarov","doi":"10.14529/mmp220208","DOIUrl":null,"url":null,"abstract":"This article describes a method for machine-readable zones location in document images based on a combination of the Hough transform and the search for feature points. The search for feature points, filtering, and clustering using the Hough transform are described step-by-step. In addition to the machine-readable zone location, we develop a solution for determining the orientation of the zone. This method is designed to meet the requirements for real-time operation on mobile devices. The paper presents the results of measuring the quality of the method on an open synthetic dataset and the operating time on mobile devices. An experimental study on an artificial dataset show that the proposed algorithm allows to achieve a quality of 0,82 in terms of the mean value of the Jaccard indices. The operating time of the proposed algorithm for machine-readable zone location on a mobile device is 6 ms on the iPhone SE 2.","PeriodicalId":44106,"journal":{"name":"Bulletin of the South Ural State University Series-Mathematical Modelling Programming & Computer Software","volume":"214 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of the South Ural State University Series-Mathematical Modelling Programming & Computer Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14529/mmp220208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 2
Abstract
This article describes a method for machine-readable zones location in document images based on a combination of the Hough transform and the search for feature points. The search for feature points, filtering, and clustering using the Hough transform are described step-by-step. In addition to the machine-readable zone location, we develop a solution for determining the orientation of the zone. This method is designed to meet the requirements for real-time operation on mobile devices. The paper presents the results of measuring the quality of the method on an open synthetic dataset and the operating time on mobile devices. An experimental study on an artificial dataset show that the proposed algorithm allows to achieve a quality of 0,82 in terms of the mean value of the Jaccard indices. The operating time of the proposed algorithm for machine-readable zone location on a mobile device is 6 ms on the iPhone SE 2.
本文介绍了一种基于霍夫变换和特征点搜索相结合的文档图像中机器可读区域定位方法。搜索特征点,过滤和聚类使用霍夫变换一步一步地描述。除了机器可读的区域位置外,我们还开发了确定区域方向的解决方案。该方法是为了满足移动设备实时操作的需求而设计的。本文给出了该方法在一个开放的合成数据集上的质量测量结果和在移动设备上的运行时间。在人工数据集上的实验研究表明,该算法可以实现Jaccard指数均值的0.82质量。在iPhone SE 2上,所提算法在移动设备上的机器可读区域定位的操作时间为6 ms。
期刊介绍:
Series «Mathematical Modelling, Programming & Computer Software» of the South Ural State University Bulletin was created in 2008. Nowadays it is published four times a year. The basic goal of the editorial board as well as the editorial commission of series «Mathematical Modelling, Programming & Computer Software» is research promotion in the sphere of mathematical modelling in natural, engineering and economic science. Priority publication right is given to: -the results of high-quality research of mathematical models, revealing less obvious properties; -the results of computational research, containing designs of new computational algorithms relating to mathematical models; -program systems, designed for computational experiments.