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iJADE authenticator - An intelligent multiagent based facial authentication system

机译:iJADE身份验证器-基于智能多代理的面部身份验证系统

摘要

In modern consumer e-shopping environments, customer authentication is a critical process for confirming the identify of the customer. Traditional authentication techniques that rely on the customers to proactively identify themselves (using various schemes) can effect the user-friendliness of the e-shopping experience, and therefore reduce the customers' preference for such facilities. In this paper, we propose an innovative intelligent multiagent-based environmental, called iJADE (intelligent Java Agent Development Environment) to provide an intelligent agent-based platform in the e-commerce environment. Contemporary agent development platforms are focused on the autonomy and mobility of the agents, whereas iJADE provides an intelligent layer (known as the "conscious layer") to implement various AI (artificial intelligence) functionalities in order to produce "smart" agents. From an implementation perspective, we introduce an innovative e-shopping authentication scheme called the "iJADE Authenticator", which is an invariant face recognition system that uses intelligent mobile agents. This system can provide fully automatic, mobile and reliable user authentication. More importantly, the authentication process can be carried out without the users necessarily being aware of it. Experimental results are presented for a database of 1 020 tested face images obtained under conditions of widely varying facial expressions, viewing perspectives and image sizes. An overall average correct recognition rate of over 90% is attained.
机译:在现代消费者电子购物环境中,客户身份验证是确认客户身份的关键过程。依赖于客户(使用各种方案)主动识别自己的传统身份验证技术可以影响电子购物体验的用户友好性,从而降低客户对此类设施的偏爱。在本文中,我们提出了一种创新的基于多代理的智能环境,称为iJADE(智能Java代理开发环境),以在电子商务环境中提供基于智能代理的平台。当代的代理开发平台专注于代理的自治性和移动性,而iJADE提供了一个智能层(称为“意识层”)来实现各种AI(人工智能)功能,以产生“智能”代理。从实现的角度,我们介绍了一种创新的电子购物身份验证方案,称为“ iJADE Authenticator”,它是使用智能移动代理的不变面部识别系统。该系统可以提供全自动,移动和可靠的用户身份验证。更重要的是,可以在用户不必意识到认证过程的情况下执行认证过程。实验结果是针对在广泛变化的面部表情,视角和图像尺寸的条件下获得的1,020张经测试的面部图像的数据库提出的。总体平均正确识别率达到90%以上。

著录项

  • 作者

    Lee RST;

  • 作者单位
  • 年度 2002
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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