scholarly journals Modelling of Facial Images for Analysis of Recognition System

2021 ◽  
Vol 2107 (1) ◽  
pp. 012041
Author(s):  
Assyakirin M H ◽  
Shafriza Nisha B ◽  
Haniza Y ◽  
Fathinul Syahir A S ◽  
Muhammad Juhairi A S
Keyword(s):  
Face Recognition ◽  
Performance Analysis ◽  
Facial Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Background Intensity ◽  
Face Recognition System ◽  
Recognition Systems ◽  
Human Faces ◽  
Facial Images

Abstract Face recognition is categorized as a biometric technology that employs the use of computer ability in image processing to detect and recognize human faces. Face recognition system has numerous applications for many purposes such as for access control, law enforcement and surveillance thus this system is dominant in present technology. Generally, face recognition system become more advance in term of the accuracy and implementation. However, there are a few parameters that effects the accuracy of recognition system for examples, the pose invariant, illumination effect, size of image and noise tolerance. Even though there are a number of systems were already available in the literature, the complete understanding of their performances are relatively limited. This is due to many systems focused on a narrow application band – therefore, a comprehensive analysis are needed in order to understand their performances leading to establishing the conditions for successful face recognition system. In this paper we developed a synthetic model to represent facial images to be used as a platform for performance analysis of facial recognition systems. The model includes 5 face types with the ability to vary all parameters that are affecting recognition performance – measurement noise, face size and face-background intensity differences. The model is important as it provide an avenue for performance analysis of facial recognition systems.

scholarly journals Multialgorithmic Frameworks for Human Face Recognition

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Radhey Shyam ◽  
Yogendra Narain Singh
Keyword(s):  
Face Recognition ◽  
Local Binary Pattern ◽  
Recognition Performance ◽  
Critical Evaluation ◽  
Recognition System ◽  
Human Face Recognition ◽  
Face Recognition System ◽  
The Face ◽  
In The Wild ◽  
Recognition Systems

This paper presents a critical evaluation of multialgorithmic face recognition systems for human authentication in unconstrained environment. We propose different frameworks of multialgorithmic face recognition system combining holistic and texture methods. Our aim is to combine the uncorrelated methods of the face recognition that supplement each other and to produce a comprehensive representation of the biometric cue to achieve optimum recognition performance. The multialgorithmic frameworks are designed to combine different face recognition methods such as (i) Eigenfaces and local binary pattern (LBP), (ii) Fisherfaces and LBP, (iii) Eigenfaces and augmented local binary pattern (A-LBP), and (iv) Fisherfaces and A-LBP. The matching scores of these multialgorithmic frameworks are processed using different normalization techniques whereas their performance is evaluated using different fusion strategies. The robustness of proposed multialgorithmic frameworks of face recognition system is tested on publicly available databases, for example, AT & T (ORL) and Labeled Faces in the Wild (LFW). The experimental results show a significant improvement in recognition accuracies of the proposed frameworks of face recognition system in comparison to their individual methods. In particular, the performance of the multialgorithmic frameworks combining face recognition methods with the devised face recognition method such as A-LBP improves significantly.

scholarly journals Reconocimiento de Facial basado en FPGA

2019 ◽  
pp. 62-67
Keyword(s):  
Face Recognition ◽  
Facial Recognition ◽  
Recognition System ◽  
Theoretical Physics ◽  
Visual Features ◽  
Parallel Processes ◽  
Face Recognition System ◽  
Fast Processing ◽  
El Sistema ◽  
Recognition Systems

Reconocimiento de Facial basado en FPGA Face Recognition based on FPGA Julio C. Molina, Miguel A. Risco Centro de Investigación y Desarrollo en Ingeniería (CIDI), Facultad de Ingeniería Electrónica y Mecatrónica de la Universidad Tecnológica del Perú (UTP) RVI Proyect from the Microprocessor Laboratory of the International Centre of Theoretical Physics(ICTP),Trieste, Italia DOI: https://doi.org/10.33017/RevECIPeru2011.0011/ RESUMEN El análisis de las imágenes es un tema en el que se está dando mucho énfasis con la finalidad de identificar parámetros, datos, características visuales en la imagen que proporcione datos del entorno que está representado en la imagen pero sin la intervención de una persona. Varios métodos han sido desarrollados con el pasar de los años, cada uno buscando minimizar el error. La gran mayoría de estos sistemas de Reconocimiento Facial han sido implementados en una computadora de escritorio y pocos han sido sobre un hardware. El presente trabajo presenta un sistema de Reconocimiento Facial basada en FPGA, La FPGA es configurada con el lenguaje VHDL, el sistema será independiente de una computadora, esto da al sistema tres principales ventajas, las cuales son la rapidez de procesamiento gracias a la capacidad de la FPGA de poder realizar procesos en paralelo, además de otras dos ventajas que son el peso y el tamaño que son importantes al tener aplicaciones muy limitadas en peso y tamaño. Descriptores: Reconocimiento Facial, Análisis de Imágenes, FPGA, VHDL. ABSTRACT The image analysis is a subject on which much emphasis is being given with purpose of identifying parameters, data, visual features in the image that provide us information about environment, it is represented in the image, but without the intervention of a person. Many methods have been developed with passing of the years, each seeking to minimize the error. The vast majority of implementations of these Facial Recognition Systems have been in a computer and a few have been implemented on hardware. This paper presents a Face Recognition System based on FPGA, The FPGA is configured with the language VHDL, this system is independent of a computer, this will give the system based on FPGA three main advantages, which include fast processing thanks to the ability of the FPGA that can perform parallel processes, and the other two advantages are the size and weight that are important to have more limited applications in weight and size. Keywords: Facial Recognition, Images Analysis, FPGA, VHDL.

scholarly journals Integarted Minimum Cost Sub-Block Matching Distance based Face Recognition using Internet of Things

2019 ◽  
Vol 8 (11) ◽  
pp. 117-122
Keyword(s):  
Face Recognition ◽  
Recognition Performance ◽  
Minimum Cost ◽  
Recognition System ◽  
Block Matching ◽  
Face Region ◽  
Input Face ◽  
Face Recognition System ◽  
The Face ◽  
Fuzzy C Means Clustering

Now a days one of the critical factors that affects the recognition performance of any face recognition system is partial occlusion. The paper addresses face recognition in the presence of sunglasses and scarf occlusion. The face recognition approach that we proposed, detects the face region that is not occluded and then uses this region to obtain the face recognition. To segment the occluded and non-occluded parts, adaptive Fuzzy C-Means Clustering is used and for recognition Minimum Cost Sub-Block Matching Distance(MCSBMD) are used. The input face image is divided in to number of sub blocks and each block is checked if occlusion present or not and only from non-occluded blocks MWLBP features are extracted and are used for classification. Experiment results shows our method is giving promising results when compared to the other conventional techniques.

scholarly journals A Web-Based Mobile Attendance System with Facial Recognition Feature

2020 ◽  
Vol 14 (05) ◽  
pp. 193
Author(s):  
Noradila Nordin ◽  
Nurul Husna Mohd Fauzi
Keyword(s):  
Face Recognition ◽  
Mobile Devices ◽  
Conventional Method ◽  
Facial Recognition ◽  
Recognition System ◽  
Web Based ◽  
Face Recognition System ◽  
The Face ◽  
System Prototype

Attendance marking in a classroom is one of the methods used to track the student’s presence in the lecture. The conventional method that is being enforced has shown to be vulnerable, inaccurate and time-consuming especially in a large classroom. It is difficult to identify absentees and proxy attendees based on the conventional attendance marking method. In order to overcome the challenges faced in the conventional method, a web-based mobile attendance system with facial recognition feature is proposed. It incorporated the existing mobile devices with a camera and the face recognition system to allow the attendance system to be used in classrooms automatically and efficiently with minor implementation requirements. The system prototype received positive responses from the volunteers who tested the system to replace the conventional attendance marking.

scholarly journals Formal Implementation of a Performance Evaluation Model for the Face Recognition System

2008 ◽  
Vol 2008 ◽  
pp. 1-10 ◽  
Author(s):  
Yong-Nyuo Shin ◽  
Jason Kim ◽  
Yong-Jun Lee ◽  
Woochang Shin ◽  
Jin-Young Choi
Keyword(s):  
Performance Evaluation ◽  
Face Recognition ◽  
Evaluation System ◽  
Performance Test ◽  
Evaluation Model ◽  
Recognition System ◽  
Performance Evaluation Model ◽  
Face Recognition System ◽  
Recognition Systems ◽  
A Performance

Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

scholarly journals Performance Improvement of Face Recognition System using Selective Local Feature Vectors

2013 ◽  
Vol 10 (2) ◽  
pp. 1330-1338
Author(s):  
Vasudha S ◽  
Neelamma K. Patil ◽  
Dr. Lokesh R. Boregowda
Keyword(s):  
Face Recognition ◽  
Performance Improvement ◽  
Recognition Rate ◽  
Recognition System ◽  
Image Splicing ◽  
Feature Vectors ◽  
Face Recognition System ◽  
Prime Concern ◽  
Wide Range ◽  
Recognition Systems

Face recognition is one of the important applications of image processing and it has gained significant attention in wide range of law enforcement areas in which security is of prime concern. Although the existing automated machine recognition systems have certain level of maturity but their accomplishments are limited due to real time challenges. Face recognition systems are impressively sensitive to appearance variations due to lighting, expression and aging. The major metric in modeling the performance of a face recognition system is its accuracy of recognition. This paper proposes a novel method which improves the recognition accuracy as well as avoids face datasets being tampered through image splicing techniques. Proposed method uses a non-statistical procedure which avoids training step for face samples thereby avoiding generalizability problem which is caused due to statistical learning procedure. This proposed method performs well with images with partial occlusion and images with lighting variations as the local patch of the face is divided into several different patches. The performance improvement is shown considerably high in terms of recognition rate and storage space by storing train images in compressed domain and selecting significant features from superset of feature vectors for actual recognition.

scholarly journals Individual identification of Japanese macaques (Macaca fuscata) using a face recognition system and a limited number of learning images

2020 ◽  
Author(s):  
Yosuke Otani ◽  
Hitoshi Ogawa
Keyword(s):  
Face Recognition ◽  
Macaca Fuscata ◽  
Field Research ◽  
Recognition System ◽  
Japanese Macaques ◽  
Individual Identification ◽  
System Construction ◽  
Face Recognition System ◽  
Recognition Systems ◽  
High Degree

AbstractIndividual identification is an important technique in animal research that requires researcher training and specialized skillsets. Face recognition systems using artificial intelligence (AI) deep learning have been put into practical use to identify in humans and animals, but a large number of annotated learning images are required for system construction. In wildlife research cases, it is difficult to prepare a large amount of learning images, which may be why systems using AI have not been widely used in field research. To investigate the development of a system that identifies individuals using a small number of learning images, we constructed a system to identify individual Japanese macaques (Macaca fuscata yakui) with a low error rate from an average of 20 images per individual. The characteristics of this system were augmentation of data, simultaneous determination by four individual identification models and identification from a majority of five frames to ensure reliability. This technology has a high degree of utility for various stakeholders and it is expected that it will advance the development of individual identification systems by AI that can be widely used in field research.

scholarly journals Real-Time Attendance and Feedback System

2021 ◽  
pp. 1135-1139
Author(s):  
Piyush Manish Sonar ◽  
Aniket Nitin Chaudhari ◽  
Mehul Deepak Sethi ◽  
Tejaswini Sanjay Gadakh
Keyword(s):  
Face Recognition ◽  
Principal Component ◽  
Feedback System ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Student Attendance ◽  
Feedback Form ◽  
Face Recognition System ◽  
User Friendly ◽  
Facial Images

Face is the representation of one’s identity. Hence, we have proposed an automated student attendance system based on face recognition. Face recognition system is very useful in life applications especially for attendance system. In our proposed approach, firstly, video framing is performed by activating the camera through a user-friendly interface. In the pre-processing stage, scaling of the size of images is performed, if necessary, in order to prevent loss of information. In face recognition stage, enhanced local binary pattern (LBP) and principal component analysis (PCA) is applied correspondingly in order to extract the features from facial images. Another way of marking the attendance is fingerprint recognition. To mark the attendance students simply have to give the fingerprint impression in fingerprint scanner module. Finally, the attendance of the recognized student will be marked and saved in the excel file. The student who is not registered will also be able to register on the spot and notification will be given if students sign in more than once. Whenever seminar is completed then a link is sent on email. It includes the information in terms of feedback. When student fills the feedback form then analysis of overall session is done.

scholarly journals Railway Access Control System using Face Recognition

2020 ◽  
Vol 9 (3) ◽  
pp. 444-448
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Modern World ◽  
Qr Code ◽  
Quick Response ◽  
Code System ◽  
Railway Station ◽  
Face Recognition System ◽  
Access Control System ◽  
Recognition Systems

Nowadays booking tickets and getting inside a railway station is adifficult task. Manual checking becomes a burden and time consuming. Also as everything is getting digitized in this modern world introduce face recognition and Quick Response (QR) code system for entry helps in passenger convenience.Face recognition is a method of identifying or verifying the identity of an individual using their face. Face recognition systems can be used to identify people in photos, video, or in real-time.So this system focuses on passengers’ convenience through allowing them to book tickets online and by introducing face recognition system and QR code system for entry to a railway station.This system helps inidentifying people who try to travel without buying tickets and also helps toapprehend the blacklisted person which increases security in the railway station. Online booking is one of the convenient ways tobook the ticket. This system also provides the convenience to passenger by issuing the digital ticket in the form of QR code thus avoiding any fuss due to the loss of the physical ticket.

scholarly journals Using Local Features in Face Recognition Systems

2018 ◽  
pp. 131-134
Author(s):  
Yildiz Aydin ◽  
Funda Akar
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Local Features ◽  
Support Vector ◽  
Global Feature ◽  
Affine Transformations ◽  
Face Recognition System ◽  
Long Time ◽  
Recognition Systems ◽  
The Many

Among the many applications in the field of computer vision, face recognition systems; is a subject that has been studied extensively and has been working for a long time. In general, the success of facial recognition systems, which consist of feature extraction and classifier steps, depends not only on the classifier but also on the features used. In a face recognition system, the feature selection is to obtain distinctive features for recognition of different facial images of interest. For this purpose, SIFT, SURF and SIFT + SURF features, which are unchanging features to scaling and affine transformations, are used in this study. In addition, to be able to compare with these local features, the HOG feature which is a global feature, also has been added to the study. Classification was performed using support vector machine. Experimental results show that local features are more successful than the global feature HOG.

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