Face Recognition Technique
2018
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Abstract
Face acknowledgment from picture or video is a famous theme in biometrics investigate. Numerous open places generally have observation cameras for video catch and these cameras have their huge incentive for security reason. It is broadly recognized that the face acknowledgment have played a vital part in reconnaissance framework as it needn't bother with the question's participation. The real points of interest of face based recognizable proof over different biometrics are uniqueness and acknowledgment. As human confront is a dynamic question having high level of fluctuation in its appearance, that makes confront recognition a troublesome issue in PC vision. In this field, precision and speed of ID is a primary issue. The objective of this paper is to assess different face recognition and acknowledgment strategies, give finish answer for picture based confront location and acknowledgment with higher precision, better reaction rate as an underlying advance for video reconnais...
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2017
In this computerized world Face acknowledgment in video has wide concentration as a secretive strategy for observation to improve security and dependability in assortment of use areas (e.g., auto crashes, airplane terminals, movement, and Terrorist assault). A video contains impermanent data and various examples of a face, so desires from this is to prompt better face acknowledgment execution as for still face pictures. Be that as it may, confronts showing up in avideo have significant varieties in stance and light. Confront identification has been finished by a few people and notwithstanding that we are learning about the Genetic calculation and their application with face acknowledgment and recognition. Keywords—Face identification, Image Enhancement, Skin Color location, Feature Extraction, Pattern Reorganization , Luminance, Color change.
2021
Measures taken in areas such as tracking personnel, patients, students, and criminals, protecting mobile devices, and combating fraud have evolved with technological developments in artificial intelligence. Today, face recognition systems are used as one of the fast and precise solutions determined for this need since the identification of the person and identity in these problems requires instantaneous and high accuracy. These systems are generally created by comparing the features in the face images taken from the picture, historical or live video with the features in the real image of the person previously taken. Face recognition systems can be integrated into many applications, as a person and identity verification may be required in almost every sector. In this study, a face recognition system was developed in order to verify the driver using public transportation in the transportation sector. In order to prevent any accident and violation caused by unauthorized driving, it has become necessary to add a personnel recognition and identity verification module to the system. For this requirement, after the driver has verified his biometric data, it was decided that the verification should be repeated instantaneously throughout the ride and at certain intervals so that the driver does not give the ride to another driver. By avoiding the methods such as a fingerprint reader and an iris verification that will distract the driver and risk the driving, a facial recognition system has been created to provide control with video images taken while driving through cameras that are currently on the vehicles and see the driver. In order to check the accuracy of the relevant system, a separate database was created for each driver, which contains images taken from videos during driving at different times. Based on a pre-trained deep learning network with pictures represents the driver, the system was tested by using test images in a database using TensorFlow and OpenCV libraries. In summary, the developed face recognition module is designed to improve the driving safety of authorized and approved personnel on the intelligent transportation system, reduce accidents caused by unauthorized users and ensure driver control.
International Journal on Recent and Innovation Trends in Computing and Communication
Generally face recognition perform many operations in our daily life such as security purpose identification of people and verification purpose. The basic aim of my project is to design an effective and secure technique for authentication using face recognition that can search or recognize a human face among the thousands of persons and improve the performance of face recognition system in low light conditions and also evaluate the performance of the designed framework by comparing the performance of existing face recognition system. This study also provides a automatic system through which a given still image or video of a scene, identify one or more persons in this scene by using a stored database of facial images.
In this paper, a facial acknowledgment framework utilizing Machine Learning is implemented, mainly using support vector machines (SVM)[7][15]. The principle goal of this task is that we can use for security purposes like mobile unlocking, biometrics and distinguishing proof of a person. With Exception Machine Learning algorithm utilizes a dataset as in data and gains from the data. Once the face is distinguished, main extraction on the face is performed utilizing histogram of gradient (HOG) which basically stores the edges of the face just as the directionality of those edges. HOG [6] [18] is a viable type of highlight extraction due its superior in normalizing neighborhood contrast. Finally, preparing and characterization of the facial information bases is finished utilizing a multi-class SVM where each exceptional face in the facial information base is a class. We endeavor to utilize this facial acknowledgment framework on various arrangements of information bases.
— in this paper We present a system for real-time, saved images And Video Recorded in this three Method We Can detecting and recognizing faces of a criminal at public place Or Checkpoint such that the system easy to learn And to implementation ,the three method that used in the system make recognition very accuracy , where if we running it will appear Login window in this screen should insert (username And Password) to enter in the main window, in the main window we must firstly insert images to Database and Then choose the way that want to recognition, if the system recognition the Face, the system will show the name of the criminal and in the same time the system will appear Danger Sound Refer that the Criminals Recognition and Matched in the Database , Besides that we can make Easy update(Rename ,Delete) to the Database without complexed. 1. Introduction Face recognition is one of the most active and widely used technique [1][2] because of its reliability and accuracy in the process of recognizing and verifying a person's identity. The need is becoming important since people are getting aware of security and privacy. For the Researchers Face Recognition is among the tedious work. It is all because the human face is very robust in nature; in fact, a person's face can change very much during short periods of time (from one day to another) and because of long periods of time (a difference of months or years). One problem of face recognition is the fact that different faces could seem very similar; therefore, a discrimination task is needed. On the other hand, when we analyze the same face, many characteristics may have changed. These changes might be because of changes in the different parameters. The parameters are: illumination, variability in facial expressions, the presence of accessories (glasses, beards, etc.); poses, age, finally background. We can divide face recognition [3][4] techniques into two big groups, the applications that required face identification and the ones that need face verification. The difference is that the first one uses a face to match with other one on a database; on the other hand, the verification technique tries to verify a human face from a given sample of that face. Face recognition has been an active research area over the last 30 years. It has been studied by scientists from different areas of psychophysical sciences and those from different areas of computer sciences. Psychologists and neuroscientists mainly deal with the human perception part of the topic, whereas engineers studying on machine recognition of human faces deal with the computational aspects of face recognition. Face recognition has applications mainly in the fields of biometrics, access control, law enforcement, and security and surveillance systems. 2. Biometric Measures Biometric systems are automated methods for identifying people through physiological or behavioral characteristics. Face recognition As compared with other biometrics systems using fingerprint/palm-print and iris, face recognition has distinct advantages because of its noncontact process. Face images can be(system would allow a person to be identified by walking in front of a camera and captured from a distance without touching the person being identified, and the identification does not require interacting with the person. In addition, face recognition serves the crime deterrent purpose because face images that have been recorded and archived can later help identify a person .
The rapid growth of information and communication technology resulted in abundant data and information growth in every field with the necessity for high data security. Face recognition is one of the types of unique biometrics measure related to human characteristics, which can be used for identification or authentication purpose as individual’s claimed identity. Face recognition system acquired great scope for the past few years in image processing for the security purposes including identification and verification process, due to its applications in various domains like crime detection, banking, and defense. Based on face data acquisition, face recognition techniques can be broadly classified into three types as intensity images using local binary pattern, video sequences using training videos and 3D information using 3D feature extraction. This paper discusses different face recognition algorithms and analyses it uses its advantages and disadvantages. This papers also compares and discusses how these techniques can be used for various identification and verification system in various fields. This paper truly attempts to disclose state of the art of face recognition technology.
International Journal of Applied Engineering and Management Letters, 2017
The rapid growth of information and communication technology resulted in abundant data and information growth in every field with the necessity for high data security. Face recognition is one of the types of unique biometrics measure related to human characteristics, which can be used for identification or authentication purpose as individual’s claimed identity. Face recognition system acquired great scope for the past few years in image processing for the security purposes including identification and verification process, due to its applications in various domains like crime detection, banking, and defense. Based on face data acquisition, face recognition techniques can be broadly classified into three types as intensity images using local binary pattern, video sequences using training videos and 3D information using 3D feature extraction. This paper discusses different face recognition algorithms and analyses it uses its advantages and disadvantages. This paper also compares and ...
2021
Background: Authentication is one of the major challenges of the information systems era. From Among other things, recognizing the human face is one of the known techniques that can be user authentication. Aim: The main purpose of this paper is to study the application of the facial recognition algorithms as a security system for the examination office at Omar Al-Mukhtar University (OMU) for the first time in Libyan universities. It can detect intruders into restricted or highly secure areas, and help reduce human errors. Methods: This system consists of two parts: the hardware part and the software part. The device part consists of a camera, while the software part consists of the face detection and facial recognition algorithms program. The face was detect using the Viola Jones method and face recognition is performed by Use of independent component analysis (ICA). When a person enters the area in question, his photos are taken by the camera and sent to the program for analysis an...

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