Indexing for Healthcare Biometric Databases

Author:

Tiwari Kamlesh1,Arora Geetika1,Gupta Phalguni2

Affiliation:

1. Birla Institute of Technology and Science, India

2. National Institute of Technical Teachers Training and Research, India

Abstract

The healthcare industry offers highly personalized services to its patients. It is necessary to correctly identify the patient and efficiently link his medical records as and when needed. It is important to note that the need of identification arises in many desperate scenarios when the patient may not be able to tell anything about himself. Biometrics can help in this scenario by using physiological or behavioral characteristics. Some of the biometrics traits could be acquired without direct participation of the person, and therefore, the patient need not provide any pin, password, or token for his identification. Biometrics can handle challenges of duplicate medical records and identity theft. However, there is an important issue that may arise when a large number of patients get registered to the system. Increase in the size of the biometric database gradually escalates the time required for identification. This calls for the need of an efficient indexing approach that can confine the search space and decrease the response time. This chapter highlights biometric indexing approaches suitable for the healthcare industry.

Publisher

IGI Global

Reference59 articles.

1. Electronic Health Records

2. Pore based indexing for High-Resolution Fingerprints.;V.Anand;IEEE International Conference on Identity, Security and Behavior Analysis (ISBA),2017

3. Score level fusion of voting strategy of geometric hashing and SURF for an efficient palmprint-based identification

4. Fast exact fingerprint indexing based on Compact Binary Minutia Cylinder Codes

5. Fingerprint identification using delaunay triangulation. International Conference on Information Intelligence and Systems.;G.Bebis;Proceedings,1999

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3