{"title":"高级图像表示中的形状识别:数据准备与识别方法框架","authors":"J. Lazarek, P. Szczepaniak","doi":"10.5220/0007579000570064","DOIUrl":null,"url":null,"abstract":"The automatic shape recognition is an important task in various image processing applications, including medical problems. Choosing the right image representation is key to the recognition process. In the paper, we focused on high-level image representation (using line segments), thanks to which the amount of data necessary for processing in subsequent stages is significantly reduced. We present the framework of recognition method with the use of graph grammars.","PeriodicalId":162397,"journal":{"name":"Bioimaging (Bristol. Print)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shape Recognition in High-level Image Representations: Data Preparation and Framework of Recognition Method\",\"authors\":\"J. Lazarek, P. Szczepaniak\",\"doi\":\"10.5220/0007579000570064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The automatic shape recognition is an important task in various image processing applications, including medical problems. Choosing the right image representation is key to the recognition process. In the paper, we focused on high-level image representation (using line segments), thanks to which the amount of data necessary for processing in subsequent stages is significantly reduced. We present the framework of recognition method with the use of graph grammars.\",\"PeriodicalId\":162397,\"journal\":{\"name\":\"Bioimaging (Bristol. Print)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioimaging (Bristol. Print)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5220/0007579000570064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioimaging (Bristol. Print)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0007579000570064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Shape Recognition in High-level Image Representations: Data Preparation and Framework of Recognition Method
The automatic shape recognition is an important task in various image processing applications, including medical problems. Choosing the right image representation is key to the recognition process. In the paper, we focused on high-level image representation (using line segments), thanks to which the amount of data necessary for processing in subsequent stages is significantly reduced. We present the framework of recognition method with the use of graph grammars.