scholarly journals Face Detection Opencv Based ATM Security System

2020 ◽  
pp. 425-432
Author(s):  
Priyadharshini R ◽  
Priyadharshini V ◽  
Vijeletchumi R ◽  
Beaulah David
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Group Action ◽  
Mobile Application ◽  
Image Steganography ◽  
Secret Key ◽  
Malicious Attacks ◽  
Security Framework ◽  
Application Management ◽  
The People

The Aim of this paper is to bolster security of the traditional cash dispenser machine (ATM) model. So a replacement is proposed that enhances the general expertise, usability and convenience of the group action at the ATM. ATM are wide used these days by the people however its exhausting to hold their ATM card all over. The user might forget their ATM PIN number. This paper is developed for identification and authentication of ATM users so creating face as key. Options like face recognition, image steganography and mobile application management are used for sweetening of privacy of users and security of accounts. Face recognition technology helps the machine to spot each and every user unambiguously. Image steganography is the technique used for the image of user by embedding it into an another image and keep. Its one among the ways utilized to guard the image of users from malicious attacks and hackers. The mobile application helps the particular account holders to supply permission to others to do the ATM transactions. The mobile application contains options like secret key and amount withdrawal to offer confirmation. It helps folks to access another person’s ATM account in emergency with their authentication. This utterly eliminates all the possibilities of fraud thanks to larceny and duplicity of the ATM cards. Moreover, the experiment is that the method in ATM security framework to enhance security and innovative ATM group action.

Face Detection With Face Mask for COVID-19 Pandemic Using Neural Networks

2022 ◽  
pp. 210-223
Author(s):  
Nitish Devendra Warbhe ◽  
Rutuja Rajendra Patil ◽  
Tarun Rajesh Shrivastava ◽  
Nutan V. Bansode
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Face Detection ◽  
Face Mask ◽  
Detection Technique ◽  
Facial Features ◽  
Feature Points ◽  
The People ◽  
Biometric Systems ◽  
The Face

The COVID-19 virus can be spread through contact and contaminated surfaces; therefore, typical biometric systems like password and fingerprint are unsafe. Face recognition solutions are safer without any need of touching any device. During the COVID-19 situation as all of the people are advised to wear masks on their faces, the existing face detection technique is not able to identify the person with face occlusion. The fraudsters and thieves take advantage of this scenario and misuse the face mask, favoring them to be able to steal and commit various crimes without being identified. Face recognition methods fail to detect or recognize the face as half of the face is masked and the features are suppressed. Face recognition requires the visibility of major facial features for face normalization, orientation correction, and recognition. Thus, the chapter focuses on the facial recognition based on the feature points surrounding the eye region rather than taking the whole face as a parameter.

Mobile Application for Displaying Voice Message on LCD Screen

2018 ◽  
Vol 6 (9) ◽  
pp. 33
Author(s):  
Rohit Kuthe ◽  
Nilesh Sonkusare ◽  
L. H. Patil
Keyword(s):  
Mobile Application ◽  
Authorized User ◽  
The People ◽  
Important Message ◽  
Electronic Display ◽  
Paper Work ◽  
Short Span ◽  
Voice Message

This paper talks about an innovative and rather an interesting manner of intimating the message to the people using the wireless electronic display on the screen. This will help us in passing any message almost immediately without any delay just by sending an SMS which is better and more reliable than the old traditional way of passing the message on a screen. Our aim is to reduce the amount of paper work and make use the possible technological resources.  In this paper, we are trying to implement our system in such a way that it can display message send from the authorized user to the various receiving ends. So spreading of important message or screen will take place within the very short span of time to respective mobile application. Means user or registered person will be able to send the message from anywhere and this message will be displayed on a screen at the respective place.

Emerging Challenges and Opportunities of Mobile Commerce in India: A Study on Societal Perspective

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Utkarsh Kumar ◽  
Anil Kumar Gope ◽  
Shweta Singh
Keyword(s):  
Growth Rate ◽  
Societal Perspective ◽  
Mobile Applications ◽  
Mobile Application ◽  
Mobile Commerce ◽  
Mobile Banking ◽  
Black And White ◽  
The People ◽  
Challenges And Opportunities

In India, the position of mobile banking was in saga and this time, it is in pic position. The speedof reaching the people is going high and high. This is time of wireless world and sense of prestige; no doubt the mobile commerce is contributing to enhance the beauty of life and playing the role of metaphor and has become the part and parcel of our life. This growth has changed people to do business in mobile commerce (М- Commerce). Peoples are transferring to M-Commerce to attain good and fast transaction into market and saving their precious time. M-Commerce has become distinguished in Indian people, quickly during last few years. Due to large number of mobile application, growth rate in mobile penetration in India is increasing with the rapid speed. The mobile users has shifted to use the android phone from simple and black and white phone and taking the service of internet, the role of telecom companies is also important in the being popular of mobile commerce. Although many people have started E-Commerce but still a separate part of the society feel uncomfortable and hesitate to use M-Commerce because of security problems, payment issues and complexity of mobile applications. This paper identifies facts about the feasibility of MCommercein India today its growth and the Strength and opportunity, weakness and threats lying ahead.

Pose estimation and frontal face detection for face recognition

2005 ◽  
Author(s):  
Eng Thiam Lim ◽  
Jiangang Wang ◽  
Wei Xie ◽  
Venkarteswarlu Ronda
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Pose Estimation

scholarly journals Full Capacity Image Steganography Using Seven-Segment Display Pattern as Secret Key

2018 ◽  
Vol 14 (6) ◽  
pp. 753-763 ◽  
Author(s):  
Mohammed A. Fadhil Al-Husainy ◽  
Hamza Abbass A. Al-Sewadi
Keyword(s):  
Image Steganography ◽  
Secret Key ◽  
Full Capacity

The Adaboost Algorithm Applied in ATM Automatic Identification System

2013 ◽  
Vol 753-755 ◽  
pp. 2941-2944
Author(s):  
Ming Hui Zhang ◽  
Yao Yu Zhang
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Computing Time ◽  
Automatic Identification ◽  
Identification System ◽  
Human Face ◽  
Detection Experiment ◽  
Adaboost Algorithm ◽  
Face Features ◽  
Human Faces

Seeing that human face features are unique, an increasing number of face recognition algorithms on existing ATM are proposed. Since face detection is a primary link of face recognition, our system adopts AdaBoost algorithm which is based on face detection. Experiment results demonstrated that the computing time of face detection using this algorithm is about 70ms, and the single and multiple human faces can be effectively measured under well environment, which meets the demand of the system.

scholarly journals Pre filtering techniques for face recognition based on edge detection algorithm

2017 ◽  
Vol 7 (1.1) ◽  
pp. 213
Author(s):  
Sheela Rani ◽  
Vuyyuru Tejaswi ◽  
Bonthu Rohitha ◽  
Bhimavarapu Akhil
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Detection Algorithm ◽  
Facial Features ◽  
Human Face ◽  
Video Frames ◽  
Similar Idea ◽  
The Individual ◽  
The Given ◽  
Interesting Area

Recognition of face has been turned out to be the most important and interesting area in research. A face recognition framework is a PC application that is apt for recognizing or confirming the presence of human face from a computerized picture, from the video frames etc. One of the approaches to do this is by matching the chosen facial features with the pictures in the database. It is normally utilized as a part of security frameworks and can be implemented in different biometrics, for example, unique finger impression or eye iris acknowledgment frameworks. A picture is a mix of edges. The curved line potions where the brightness of the image change intensely are known as edges. We utilize a similar idea in the field of face-detection, the force of facial colours are utilized as a consistent value. Face recognition includes examination of a picture with a database of stored faces keeping in mind the end goal to recognize the individual in the given input picture. The entire procedure covers in three phases face detection, feature extraction and recognition and different strategies are required according to the specified requirements.

Research and Implementation of Face Detection Based on OpenCV

2014 ◽  
Vol 971-973 ◽  
pp. 1710-1713
Author(s):  
Wen Huan Wu ◽  
Ying Jun Zhao ◽  
Yong Fei Che
Keyword(s):  
Face Recognition ◽  
Detailed Analysis ◽  
Real Time ◽  
Face Detection ◽  
Recognition System ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Accuracy Rate ◽  
Face Recognition System ◽  
The Face

Face detection is the key point in automatic face recognition system. This paper introduces the face detection algorithm with a cascade of Adaboost classifiers and how to configure OpenCV in MCVS. Using OpenCV realized the face detection. And a detailed analysis of the face detection results is presented. Through experiment, we found that the method used in this article has a high accuracy rate and better real-time.

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