{"title":"结合局部质量度量和全局约束的高质量矢量化","authors":"M. Röösli, G. Monagan","doi":"10.1109/ICDAR.1995.598986","DOIUrl":null,"url":null,"abstract":"We present a vectorization system to generate vector data which corresponds to the line structures of a raster image. The vector data consists of the primitives: \"straight lane segment\" and \"circular arc\". The vectorization system measures the quality of each primitive generated. Thus, the vectorization does not only produce high quality vector data, it also gives a precise description of the quality of the data generated. This is crucial if the requirements set by industrial applications are to be met. In order not to lose the quality of the vector data while constructing primitives into line objects, geometric constraints are incorporated already at the vectorization level: constraints like requiring segments to be parallel or perpendicular, circular arcs to be concentric, or tangents of the primitives to be equal at their connection point. After the constraints have been satisfied the resulting primitives still fulfil the quality requirements as before the constraints were imposed. The possibility to refit the generated vector data under adapted constraints allows for an efficient interactive postprocessing of the data.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"435 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A high quality vectorization combining local quality measures and global constraints\",\"authors\":\"M. Röösli, G. Monagan\",\"doi\":\"10.1109/ICDAR.1995.598986\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a vectorization system to generate vector data which corresponds to the line structures of a raster image. The vector data consists of the primitives: \\\"straight lane segment\\\" and \\\"circular arc\\\". The vectorization system measures the quality of each primitive generated. Thus, the vectorization does not only produce high quality vector data, it also gives a precise description of the quality of the data generated. This is crucial if the requirements set by industrial applications are to be met. In order not to lose the quality of the vector data while constructing primitives into line objects, geometric constraints are incorporated already at the vectorization level: constraints like requiring segments to be parallel or perpendicular, circular arcs to be concentric, or tangents of the primitives to be equal at their connection point. After the constraints have been satisfied the resulting primitives still fulfil the quality requirements as before the constraints were imposed. The possibility to refit the generated vector data under adapted constraints allows for an efficient interactive postprocessing of the data.\",\"PeriodicalId\":273519,\"journal\":{\"name\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"volume\":\"435 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.1995.598986\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.1995.598986","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A high quality vectorization combining local quality measures and global constraints
We present a vectorization system to generate vector data which corresponds to the line structures of a raster image. The vector data consists of the primitives: "straight lane segment" and "circular arc". The vectorization system measures the quality of each primitive generated. Thus, the vectorization does not only produce high quality vector data, it also gives a precise description of the quality of the data generated. This is crucial if the requirements set by industrial applications are to be met. In order not to lose the quality of the vector data while constructing primitives into line objects, geometric constraints are incorporated already at the vectorization level: constraints like requiring segments to be parallel or perpendicular, circular arcs to be concentric, or tangents of the primitives to be equal at their connection point. After the constraints have been satisfied the resulting primitives still fulfil the quality requirements as before the constraints were imposed. The possibility to refit the generated vector data under adapted constraints allows for an efficient interactive postprocessing of the data.