Local Binary Pattern Histogram Based Web Facial Authentication System

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Abstract

The objective of the project is to Detect and Recognize Human Facial Features via a Camera. The basic concept of this project is:- To convert the input image to HSV format to extract the binary image and additionally remove the noise from binary image using morphological operations and finally then contours are used to segment out the region of interest and further the region is analyzed to get the final result. While biometric data is generally considered one of the most reliable authentication methods, it also carries significant risk. That’s because if someone’s credit card details are hacked, that person has the option to freeze their credit and take steps to change the personal information that was breached. What do you do if you lose your digital ‘face’? Around the world, biometric information is being captured, stored, and analyzed in increasing quantities, often by organizations and governments, with a mixed record on cybersecurity. A question increasingly being asked is, how safe is the infrastructure that holds and processes all this data? As facial recognition software is still in its relative infancy, the laws governing this area are evolving (and sometimes non-existent).
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基于局部二值模式直方图的Web人脸认证系统
该项目的目标是通过摄像头检测和识别人类的面部特征。该项目的基本概念是:-将输入图像转换为HSV格式提取二值图像,并使用形态学操作去除二值图像中的噪声,最后使用轮廓分割出感兴趣的区域,并进一步对该区域进行分析,从而得到最终结果。虽然生物识别数据通常被认为是最可靠的身份验证方法之一,但它也有很大的风险。这是因为如果某人的信用卡信息被黑客入侵,该人可以选择冻结他们的信用,并采取措施更改被泄露的个人信息。如果你失去了你的数字“脸”,你该怎么办?在世界各地,生物特征信息正在被越来越多地捕获、存储和分析,通常是由组织和政府进行的,在网络安全方面的记录好坏参半。一个越来越多的问题是,保存和处理所有这些数据的基础设施有多安全?由于面部识别软件仍处于相对初级阶段,管理这一领域的法律还在不断发展(有时甚至不存在)。
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