{"title":"From ligatures to characters: a shape-based algorithm for handwriting segmentation","authors":"C. Stefano, A. Marcelli","doi":"10.1109/IWFHR.2002.1030955","DOIUrl":null,"url":null,"abstract":"This paper presents a method for locating the points where most likely joints between successive characters within a word occur. The proposed method, whose basic assumptions follow from handwriting generation studies, relies upon a set of morphological criteria applied to both the ligatures and the terminal regions of successive characters in order to decide the most appropriate position for the segmentation points. It does not exploit any temporal information, but rather it manipulates shape information, thus is suitable for both online and off-line handwriting processing. An experimental procedure, adopted to quantitatively evaluate the performance of the proposed algorithm without using any classification method, is also introduced.","PeriodicalId":114017,"journal":{"name":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWFHR.2002.1030955","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a method for locating the points where most likely joints between successive characters within a word occur. The proposed method, whose basic assumptions follow from handwriting generation studies, relies upon a set of morphological criteria applied to both the ligatures and the terminal regions of successive characters in order to decide the most appropriate position for the segmentation points. It does not exploit any temporal information, but rather it manipulates shape information, thus is suitable for both online and off-line handwriting processing. An experimental procedure, adopted to quantitatively evaluate the performance of the proposed algorithm without using any classification method, is also introduced.