{"title":"Striation Patterns Classification of Tool Marks Based on Extended Fractal Analysis","authors":"Min Yang, Donghong Li, Li Mou, Wei-dong Wang","doi":"10.1109/CCPR.2008.93","DOIUrl":null,"url":null,"abstract":"Currently, optical device, such as microscopes and CCD cameras, are utilized for identification of tool marks in the field of forensic science which mainly depend on the experience of forensic scientists. A new approach using extended fractal analysis technology to classify tool marks such as striation patterns is presented. it computes four directional multi-scale extended fractal parameters and the maximum direction fractal feature, then performs a supervised classification. Experimental results demonstrate that this method provides a classification scheme that performs well than the traditional schemes and is effective for classification of tool marks.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Chinese Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPR.2008.93","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Currently, optical device, such as microscopes and CCD cameras, are utilized for identification of tool marks in the field of forensic science which mainly depend on the experience of forensic scientists. A new approach using extended fractal analysis technology to classify tool marks such as striation patterns is presented. it computes four directional multi-scale extended fractal parameters and the maximum direction fractal feature, then performs a supervised classification. Experimental results demonstrate that this method provides a classification scheme that performs well than the traditional schemes and is effective for classification of tool marks.