scholarly journals Intruder detection and recognition using different image processing techniques for a proactive surveillance

2021 ◽  
Vol 24 (2) ◽  
pp. 843
Author(s):  
Nelson C. Rodelas ◽  
Melvin A. Ballera
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Face Detection ◽  
Research Problem ◽  
Recognition Algorithm ◽  
Evaluation Framework ◽  
Image Processing Techniques ◽  
Face Detection And Recognition ◽  
Processing Techniques ◽  
Detection And Recognition

To innovate a proactive surveillance camera, there is a need for efficient face detection and recognition algorithm. The researchers used one of the ViolaJones algorithm and used different image processing techniques to recognize intruders or not. The goal of the research is to recognize the fastest way on how the homeowners will be informed if an intruder or burglar enters their home using a proactive surveillance device. This device was programmed based on the different recognition algorithms and a criteria evaluation framework that could recognize intruders and burglars and the design used was developmental research to satisfy the research problem. The researchers used the Viola-Jones algorithm for face detection and five algorithms for face recognition. The criteria evaluation was used to identify the best face recognition algorithm and was tested in a real-world situation and captured a series of images camera and processed by proactive face detection and recognition. The result shows that the system can detect and recognize intruders and proactively send a notification to the homeowners via mobile application. It is concluded that the system can recognize the intruders and proactively notify the household members using the mobile applications and activate the alarm system of the house.

FACE DETECTION AND RECOGNITION USING MAXIMUM LIKELIHOOD CLASSIFIERS ON GABOR GRAPHS

2009 ◽  
Vol 23 (03) ◽  
pp. 433-461 ◽  
Author(s):  
MANUEL GÜNTHER ◽  
ROLF P. WÜRTZ
Keyword(s):  
Face Recognition ◽  
Maximum Likelihood ◽  
Face Detection ◽  
Recognition System ◽  
Similarity Functions ◽  
Expression Variation ◽  
Face Recognition System ◽  
Face Detection And Recognition ◽  
Ml Estimator ◽  
Detection And Recognition

We present an integrated face recognition system that combines a Maximum Likelihood (ML) estimator with Gabor graphs for face detection under varying scale and in-plane rotation and matching as well as a Bayesian intrapersonal/extrapersonal classifier (BIC) on graph similarities for face recognition. We have tested a variety of similarity functions and achieved verification rates (at FAR 0.1%) of 90.5% on expression-variation and 95.8% on size-varying frontal images within the CAS-PEAL database. Performing Experiment 1 of FRGC ver2.0, the method achieved a verification rate of 72%.

scholarly journals An Efficient Method for Multiple Face Detection & Recognition

2019 ◽  
Vol 9 (1S3) ◽  
pp. 474-478
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Efficient Method ◽  
Recognition Rate ◽  
The Future ◽  
Web Camera ◽  
The Face ◽  
Face Detection And Recognition ◽  
Future Work ◽  
Detection And Recognition

The problem of Face detection and recognition is becoming a challenge due to the wide variety of faces and the complexity of the noises and background of image. In this paper we have used C-sharp and Haar algorithm to detect the face. First in this paper the image is taken with a web-camera, storing it in the database and then once again when the person comes in the frame the name of the person is displayed. This paper is done in C-sharp which was a bit difficult for us to do and we have combined both the face detection and the recognition. The proposed method has good output and a good recognition rate. The limitation of the paper is that it does not display the name of the person above the face. In the future work will be carried on the above said topic. While developing the code some sample codes in python but those were basic programs. So this paper aims to find a solution for it and developed in C-sharp. In finding the XML file of haarcascade frontal face detection we found some problems and had to do a bit of research in finding it. The code for face detection and face recognition were found in different places and in this paper the codes for the both has been combined and found some difficulty. To overcome the basic programs we have written the code in C-sharp and the difficulty which we faced in combining the two codes have been solved. The solution has been successfully implemented and the code is fully running and the output has been successfully achieved.

MULTI-STEP FACE RECOGNITION FOR IMPROVING FACE DETECTION AND RECOGNITION RATE

2016 ◽  
Vol 16 (3) ◽  
pp. 471-491 ◽  
Author(s):  
Aigerim Altayeva ◽  
Batyrkhan Omarov ◽  
Hyeong Chul Jeong ◽  
Young Im Cho
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Recognition Rate ◽  
Face Detection And Recognition ◽  
Detection And Recognition

scholarly journals Smart Adoption System using Image Processing Techniques

2019 ◽  
Vol 8 (6S) ◽  
pp. 84-87
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Rapid Evolution ◽  
Recognition Algorithm ◽  
Ethical Challenges ◽  
Evolution Of Technology ◽  
Child Adoption ◽  
A New Technique ◽  
Processing Techniques ◽  
Adoption System

Adoption of child plays a major role in recent times. This is due to the emotional and ethical challenges faced by both the adopting parent and the children .This paper presents a new technique of applying image processing technology that uses an image based approach to the system. With the rapid evolution of technology there are large numbers of face recognition algorithm. In this paper we have attempted to review the best face recognition algorithm by considering all the algorithm and its functions. Viola Jones algorithm is used to develop the entire system. Using this algorithm image processing is implemented for further enhancement of the system .This lowers the complexity in the child adoption system and also helps to increase the efficiency of the system.

scholarly journals Face with Mask Detection and Recognition for Smart Attendance System

2021 ◽  
Vol 9 (VII) ◽  
pp. 1586-1591
Author(s):  
Shweta Panjabrao Dhawale
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Face Recognition ◽  
Face Detection ◽  
Face Mask ◽  
Learning Framework ◽  
The Face ◽  
Face Detection And Recognition ◽  
Python Programming ◽  
Detection And Recognition

In this paper we will see the face mask detection and recognition for smart attendance system. In current pandemic situation our proposed system is very useful. We have used here face algorithm technique, python programming and to capture the images open cv is used., open cv2 now comes with a very new face recognizer class for the face recognition and popular computer vision liberaay started by intel in 1999. Open cv released under BSD licence that’s why used in the academic projects. We have used the concept of deep learning framework for the detection of faces. our aim is to present the study of previous attempts at face detection and recognition for smart attendance system by using deep learning .these is rapidly growing technology with its application in various aspects.

scholarly journals Challenges in Face Detection and Recognition techniques

2020 ◽  
Vol 9 (8) ◽  
pp. 221-224
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Recognition System ◽  
Research Paper ◽  
Facial Features ◽  
Image Information ◽  
Public Crisis ◽  
Face Recognition System ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Face Recognition System is popular topic in the biometric world .This system provide Features to detect the person’s face and identify on basis of existing records in database .The aim of this study is to described how to show various facial features of an image. Face Recognition system, based on Biometric AI, uniquely finds out a person by analyzing the person's facial textures and shape. In this paper, our aim is to study various face detect and recognition techniques such as Harr Like Feature Algorithm resulting to retort criminality and public crisis. Also, some facial recognition approaches PCA and LDA have been discussed in the research paper for abstracting the image information.

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