{"title":"基于摄像机的图形符号检测","authors":"Marçal Rusiñol, J. Lladós, P. Dosch","doi":"10.1109/ICDAR.2007.76","DOIUrl":null,"url":null,"abstract":"In this paper we present a method to locate and recognize graphical symbols appearing in real images. A vectorial signature is defined to describe graphical symbols. It is formulated in terms of accumulated length and angular information computed from polygonal approximation of contours. The proposed method aims to locate and recognize graphical symbols in cluttered environments at the same time, without needing a segmentation step. The symbol signature is tolerant to rotation, scale, translation and to distortions such as weak perspective, blurring effect and illumination changes usually present when working with scenes acquired with low resolution cameras in open environments.","PeriodicalId":279268,"journal":{"name":"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Camera-Based Graphical Symbol Detection\",\"authors\":\"Marçal Rusiñol, J. Lladós, P. Dosch\",\"doi\":\"10.1109/ICDAR.2007.76\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a method to locate and recognize graphical symbols appearing in real images. A vectorial signature is defined to describe graphical symbols. It is formulated in terms of accumulated length and angular information computed from polygonal approximation of contours. The proposed method aims to locate and recognize graphical symbols in cluttered environments at the same time, without needing a segmentation step. The symbol signature is tolerant to rotation, scale, translation and to distortions such as weak perspective, blurring effect and illumination changes usually present when working with scenes acquired with low resolution cameras in open environments.\",\"PeriodicalId\":279268,\"journal\":{\"name\":\"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.2007.76\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2007.76","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we present a method to locate and recognize graphical symbols appearing in real images. A vectorial signature is defined to describe graphical symbols. It is formulated in terms of accumulated length and angular information computed from polygonal approximation of contours. The proposed method aims to locate and recognize graphical symbols in cluttered environments at the same time, without needing a segmentation step. The symbol signature is tolerant to rotation, scale, translation and to distortions such as weak perspective, blurring effect and illumination changes usually present when working with scenes acquired with low resolution cameras in open environments.