RETRACTED ARTICLE: Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things

被引:0
|
作者
Priyan Malarvizhi Kumar
Ushadevi Gandhi
R. Varatharajan
Gunasekaran Manogaran
Jidhesh R.
Thanjai Vadivel
机构
[1] VIT University,
[2] Sri Ramanujar Engineering College,undefined
[3] VelTech University,undefined
来源
Cluster Computing | 2019年 / 22卷
关键词
Global positioning system; Internet of Things; Face recognition; Feature extraction; Training module; Navigation; Neural learning; Neural network; Smartphone; Ultrasonic sensor;
D O I
暂无
中图分类号
学科分类号
摘要
Most of the advancements are now carried out by interconnecting physical devices with computers; this is what known as Internet of Things (IoT). The major problems facing by blind people fall in the category of navigating through indoor and outdoor environments consisting of various obstacles and recognition of person in front of them. Identification of objects or person only with perceptive and audio information is difficult. An intelligent, portable, less expensive, self-contained navigation and face recognition system is highly demanded for blind people. This helps blind people to navigate with the help of a Smartphone, global positioning system (GPS) and a system equipped with ultrasonic sensors. Face recognition can be done using neural learning techniques with feature extraction and training modules. The images of friends, relatives are stored in the database of user Smartphone. Whenever a person comes in front of the blind user, the application with the help of neural network gives the voice aid to the user. Thus this system can replace the regular imprecise use of guide dogs as well as white sticks to help the navigation and face recognition process for people with impaired vision.In this paper, we have proposed a novel image recognition and navigation system which provides precise and quick messages in the form of audio to visually challenged people so that they can navigate easily. The performance of the proposed method is comparatively analyzed with the help of ROC analysis.
引用
收藏
页码:7733 / 7744
页数:11
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