{"title":"Improved Palmprint Segmentation for Robust Identification and Verification","authors":"Dane Brown, K. Bradshaw","doi":"10.1109/SITIS.2019.00013","DOIUrl":null,"url":null,"abstract":"This paper introduces an improved approach to palmprint segmentation. The approach enables both contact and contactless palmprints to be segmented regardless of constraining finger positions or whether fingers are even depicted within the image. It is compared with related systems, as well as more comprehensive identification tests, that show consistent results across other datasets. Experiments include contact and contactless palmprint images. The proposed system achieves highly accurate classification results, and highlights the importance of effective image segmentation. The proposed system is practical as it is effective with small or large amounts of training data.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2019.00013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper introduces an improved approach to palmprint segmentation. The approach enables both contact and contactless palmprints to be segmented regardless of constraining finger positions or whether fingers are even depicted within the image. It is compared with related systems, as well as more comprehensive identification tests, that show consistent results across other datasets. Experiments include contact and contactless palmprint images. The proposed system achieves highly accurate classification results, and highlights the importance of effective image segmentation. The proposed system is practical as it is effective with small or large amounts of training data.