{"title":"基于贝叶斯模型的文档标识检测与识别","authors":"Hongye Wang","doi":"10.1109/ICPR.2010.483","DOIUrl":null,"url":null,"abstract":"This paper presents a simple, dynamic approach to logo detection and recognition in document images. Although there are literatures on both logo detection and logo recognition issues, Current methods lack the adaptability to variable real-world documents. In this paper we initially observe this deficiency from a different point of view and reveal its inherent causation. Then we reorganize the structure of the logo detection and recognition procedures and integrate them into a unified framework. By applying feedback and selecting proper features, we make our framework dynamic and interactive. Experiments show that the proposed method outperforms existing methods in document processing domain.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Document Logo Detection and Recognition Using Bayesian Model\",\"authors\":\"Hongye Wang\",\"doi\":\"10.1109/ICPR.2010.483\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a simple, dynamic approach to logo detection and recognition in document images. Although there are literatures on both logo detection and logo recognition issues, Current methods lack the adaptability to variable real-world documents. In this paper we initially observe this deficiency from a different point of view and reveal its inherent causation. Then we reorganize the structure of the logo detection and recognition procedures and integrate them into a unified framework. By applying feedback and selecting proper features, we make our framework dynamic and interactive. Experiments show that the proposed method outperforms existing methods in document processing domain.\",\"PeriodicalId\":309591,\"journal\":{\"name\":\"2010 20th International Conference on Pattern Recognition\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 20th International Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2010.483\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 20th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2010.483","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Document Logo Detection and Recognition Using Bayesian Model
This paper presents a simple, dynamic approach to logo detection and recognition in document images. Although there are literatures on both logo detection and logo recognition issues, Current methods lack the adaptability to variable real-world documents. In this paper we initially observe this deficiency from a different point of view and reveal its inherent causation. Then we reorganize the structure of the logo detection and recognition procedures and integrate them into a unified framework. By applying feedback and selecting proper features, we make our framework dynamic and interactive. Experiments show that the proposed method outperforms existing methods in document processing domain.