{"title":"A Novel Biological Recognition Method Based on Cranio-maxillo-facial Feature Information","authors":"Liwen Huang, Jing Yang, Xiaolong Wu, Xiaoqian Hu","doi":"10.1109/ITNG.2009.22","DOIUrl":null,"url":null,"abstract":"Recently the multi-model recognition has been considered the development trend for the fast-developing biological recognition technology. Taking humanity cranio-maxillo-facial as the target, a novel recognition method is proposed in this paper. Starting from the mathematical model based on extracting characteristic parameters, the types of characteristic parameters is determined, and the features of different parameters are analyzed. Meanwhile the computational method of related parameters has been completed. Finally, a new recognition algorithm based on these parameters is proposed and our preliminary simulation results indicate that this algorithm is effective.","PeriodicalId":347761,"journal":{"name":"2009 Sixth International Conference on Information Technology: New Generations","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Sixth International Conference on Information Technology: New Generations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNG.2009.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Recently the multi-model recognition has been considered the development trend for the fast-developing biological recognition technology. Taking humanity cranio-maxillo-facial as the target, a novel recognition method is proposed in this paper. Starting from the mathematical model based on extracting characteristic parameters, the types of characteristic parameters is determined, and the features of different parameters are analyzed. Meanwhile the computational method of related parameters has been completed. Finally, a new recognition algorithm based on these parameters is proposed and our preliminary simulation results indicate that this algorithm is effective.