A. Mostayed, Sikyung Kim, M.M. Gani Mazumder, Se Jin Park
{"title":"Foot Step Based Person Identification Using Histogram Similarity and Wavelet Decomposition","authors":"A. Mostayed, Sikyung Kim, M.M. Gani Mazumder, Se Jin Park","doi":"10.1109/ISA.2008.46","DOIUrl":null,"url":null,"abstract":"Research in person identification and authentication has attracted significant attention from the researchers and scientists. This paper presents a biometric user authentication based on a person's foot step. The advantage of this recognition method over other types of biometrics is that it enables unobtrusive user authentication where other types of biometrics are not available. Firstly the ground reaction force data was extracted using force plate to gather ground reaction force for individuals. Later we utilized the discrete wavelet transform to de-noise the experimental data and in the final step, histograms were used to identify different person's foot step. The experimental results show improvements in identification accuracies compared to previously reported work.","PeriodicalId":212375,"journal":{"name":"2008 International Conference on Information Security and Assurance (isa 2008)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Information Security and Assurance (isa 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISA.2008.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32
Abstract
Research in person identification and authentication has attracted significant attention from the researchers and scientists. This paper presents a biometric user authentication based on a person's foot step. The advantage of this recognition method over other types of biometrics is that it enables unobtrusive user authentication where other types of biometrics are not available. Firstly the ground reaction force data was extracted using force plate to gather ground reaction force for individuals. Later we utilized the discrete wavelet transform to de-noise the experimental data and in the final step, histograms were used to identify different person's foot step. The experimental results show improvements in identification accuracies compared to previously reported work.