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首页> 外文期刊>Research journal of applied science, engineering and technology >Accessing Social Network Sites Using Work Smartphone for Face Recognition and Authentication
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Accessing Social Network Sites Using Work Smartphone for Face Recognition and Authentication

机译:使用Work Smartphone进行人脸识别和身份验证访问社交网站

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摘要

Nowadays, Social Networking Sites (SNS) are increasingly getting the attention of academic, industrial researchers intrigued by their affordances and gradually gaining its importance and became a major method used to share thoughts, video, image, etc., in various domains such as research, politics, religion, academics and development. Apart of its strength points SNS has one major drawback which is the inefficient authentication of users to login. Due to this drawback; different types of fake message, non-social activities, national or personal threats, Numbers, videos and other important things are used for extortion people, which can be posted by some imposters or non-social personals. In spite of the importance of authentication in the social network, a handful number of researches conducted such accessing social network using efficient authentication technique to solve this problem. This study proposed a method to access a social network sites (such as Facebook and twitter) using face recognition techniques at the time of login in the site by Smartphones. Where Local Binary Pattern (LBP) was used to detect users face and the LBP histogram was used for features extraction. The proposed method obtained very promising results in term of accuracy (93.5%) and effectiveness for authentication of user identity.
机译:如今,社交网站(SNS)越来越受到学术,工业研究人员的关注,他们的能力引起了他们的兴趣,并逐渐获得其重要性,并成为在研究等各个领域共享思想,视频,图像等的主要方法。 ,政治,宗教,学者和发展。 SNS的一大优点是用户登录的身份验证效率低。由于这个缺点;不同类型的虚假信息,非社会活动,国家或个人威胁,数字,视频和其他重要事物被用于勒索他人,一些冒名顶替者或非社会人士可能会张贴这些信息。尽管认证在社交网络中很重要,但为数不多的研究使用有效的认证技术进行了这样的访问社交网络来解决这个问题。这项研究提出了一种在智能手机登录网站时使用面部识别技术访问社交网站(例如Facebook和Twitter)的方法。其中使用本地二进制模式(LBP)检测用户的脸部,并使用LBP直方图进行特征提取。提出的方法在准确性(93.5%)和用户身份验证的有效性方面都获得了非常有希望的结果。

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