scholarly journals PERBANDINGAN METODE PENGENALAN WAJAH MELALUI SURVEILLANCE BERBASIS PENGENALAN WAJAH

2021 ◽  
Vol 4 (1) ◽  
pp. 88-98
Author(s):  
I Nyoman Tri Anindia Putra ◽  
Ketut Sepdyana Kartini
Keyword(s):  
Real Time ◽  
Local Binary Pattern ◽  
Facial Recognition ◽  
Rejection Rate ◽  
Personal Identification ◽  
Surveillance Systems ◽  
Recognition Method ◽  
Lighting Conditions ◽  
Average Accuracy ◽  
Time Accuracy

Until now, the facial recognition method is still very difficult to do, especially when the facial confirmation process is accurate in real time. Facial recognition methods that have been tested, such as eigenface, Local Binary Pattern Histogram (LBPH), and fisherface, are feasible methods to be tested directly by applying these three methods to facial recognition-based surveillance systems. This study aims to compare the level of real-time accuracy in personal identification on the three methods through 4 parameters, namely accuracy, FAR (False Acceptance Rate), FRR (False Rejection Rate), and time condition, namely lighting conditions based on time, namely morning, noon, afternoon and evening. Based on the results of the tests that have been done, the average accuracy is obtained, namely the highest average with the eigenface method with an accuracy of 73.64%, FAR 0.11%, FRR 0.15%, the LBPH method obtains the highest average with an accuracy of 80, 91%, FAR 0.13%, FRR 0.07%, and finally fisherface got the highest average with 90.00% accuracy, 0.05% FAR, 0.05% FRR, in identifying personal. The results obtained by the Fisherface method tend to have the highest accuracy value based on the average both in terms of accuracy and the lighting conditions that have been tested.

scholarly journals Preprocessing With Symmetrical Face And Gamma Correction For Face Recognition Under Varying Illumination With Robust Regression Classification

Kursor ◽  
2018 ◽  
Vol 9 (2) ◽  
Author(s):  
Eva Y Puspaningrum ◽  
Budi Nugroho ◽  
Andri Istifariyanto
Keyword(s):  
Face Recognition ◽  
Robust Regression ◽  
Facial Recognition ◽  
Face Image ◽  
Lighting Conditions ◽  
Average Accuracy ◽  
The Face ◽  
Symmetrical Object ◽  
The Right ◽  
Symmetric Property

Facial recognition is one of the most popular issues in the field of pattern recognition.Face recognition with uncontrolled lighting conditions is more significant than thephysical characteristics of individual faces. Uncontrolled lighting from the right and leftcan affect the face image. A lot of research on facial recognition, but little attention givento the face image is symmetrical object. Several studies to explore and exploit thesymmetrical properties of the face for face recognition were performed. In this paper, wepropose a pre-processing method to solve one of the common problems in facial imageswith varying illumination. We utilize the symmetric property of the face then performedgamma correction then classified using Robust Regression. The results of this experimentgot an average accuracy of 94.31% and the proposed technique improves recognitionaccuracy especially in images with extreme lighting conditions using gamma correctionparameters γ = 0.3.

Real-time Corridor Recognition for Autonomous Vehicle

2001 ◽  
Vol 13 (4) ◽  
pp. 357-370 ◽  
Author(s):  
Mamoru Minami ◽  
◽  
Julien Agbanhan ◽  
Hidekazu Suzuki ◽  
Toshiyuki Asakura ◽  
...  
Keyword(s):  
Real Time ◽  
Autonomous Vehicle ◽  
Ccd Camera ◽  
Recognition System ◽  
Working Environment ◽  
Model Matching ◽  
Recognition Method ◽  
Matching Method ◽  
Lighting Condition ◽  
Lighting Conditions

Recognition of a working environment is critical for an autonomous vehicle such as a mobile robot to guide it along corridor and to confirm its possible intelligence. Therefore it is necessary to equip a recognition system with sensor that collect environmental information. As an effective sensor a CCD camera is generally useful for all kinds of mobile robots. However, it is hard to use the CCD camera for visual feedback since it requires to acquire information in real-time, and moreover to be robust against lighting condition varieties. This research presents a corridor recognition method using unprocessed gray-scale image, termed a raw image, and a genetic algorithm (GA), without any image information conversion, to conduct the recognition process in real-time. To achieve robustness concerning lighting condition varieties, we propose a model-matching method using a representative object model designated here as surface-strips model. The robustness of the method against noise in the environment, including lighting conditions variations, and the effectiveness of the method for real-time recognition have been verified using real corridor images.

Grenzüberschreitendes real-time Surveillance-Systems für Infektionskrankheiten

2011 ◽  
Vol 73 (03) ◽  
Author(s):  
H Freund ◽  
V Bochat ◽  
H ter Waarbeek
Keyword(s):  
Real Time ◽  
Surveillance Systems

Facial recognition technologies and the new physiognomic era

2020 ◽  
Vol 43 (2) ◽  
pp. 45-56
Author(s):  
Abigail Nieves Delgado
Keyword(s):  
Facial Recognition ◽  
Personal Identification ◽  
Digital Photographs ◽  
Different Types ◽  
Recognition Systems ◽  
The Way

The current overproduction of images of faces in digital photographs and videos, and the widespread use of facial recognition technologies have important effects on the way we understand ourselves and others. This is because facial recognition technologies create new circulation pathways of images that transform portraits and photographs into material for potential personal identification. In other words, different types of images of faces become available to the scrutiny of facial recognition technologies. In these new circulation pathways, images are continually shared between many different actors who use (or abuse) them for different purposes. Besides this distribution of images, the categorization practices involved in the development and use of facial recognition systems reinvigorate physiognomic assumptions and judgments (e.g., about beauty, race, dangerousness). They constitute the framework through which faces are interpreted. This paper shows that, because of this procedure, facial recognition technologies introduce new and far-reaching »facialization« processes, which reiterate old discriminatory practices.

Malaria elimination in India requires additional surveillance mechanisms

2021 ◽  
Author(s):  
Manju Rahi ◽  
Payal Das ◽  
Amit Sharma
Keyword(s):  
Real Time ◽  
Malaria Elimination ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Malaria Surveillance ◽  
Aggregated Data ◽  
Malaria Burden ◽  
The Core ◽  
Reporting Systems ◽  
Geographic Regions

Abstract Malaria surveillance is weak in high malaria burden countries. Surveillance is considered as one of the core interventions for malaria elimination. Impressive reductions in malaria-associated morbidity and mortality have been achieved across the globe, but sustained efforts need to be bolstered up to achieve malaria elimination in endemic countries like India. Poor surveillance data become a hindrance in assessing the progress achieved towards malaria elimination and in channelizing focused interventions to the hotspots. A major obstacle in strengthening India’s reporting systems is that the surveillance data are captured in a fragmented manner by multiple players, in silos, and is distributed across geographic regions. In addition, the data are not reported in near real-time. Furthermore, multiplicity of malaria data resources limits interoperability between them. Here, we deliberate on the acute need of updating India’s surveillance systems from the use of aggregated data to near real-time case-based surveillance. This will help in identifying the drivers of malaria transmission in any locale and therefore will facilitate formulation of appropriate interventional responses rapidly.

scholarly journals Improving 3D-3D facial registration methods: potential role of three-dimensional models in personal identification of the living

2021 ◽  
Author(s):  
Daniele Gibelli ◽  
Andrea Palamenghi ◽  
Pasquale Poppa ◽  
Chiarella Sforza ◽  
Cristina Cattaneo ◽  
...  
Keyword(s):  
Three Dimensional ◽  
3D Models ◽  
Personal Identification ◽  
Surveillance Systems ◽  
3D Registration ◽  
Three Dimensional Models ◽  
Point To Point ◽  
Point Distance ◽  
Male Subjects

AbstractPersonal identification of the living from video surveillance systems usually involves 2D images. However, the potentiality of three-dimensional facial models in gaining personal identification through 3D-3D comparison still needs to be verified. This study aims at testing the reliability of a protocol for 3D-3D registration of facial models, potentially useful for personal identification. Fifty male subjects aged between 18 and 45 years were randomly chosen from a database of 3D facial models acquired through stereophotogrammetry. For each subject, two acquisitions were available; the 3D models of faces were then registered onto other models belonging to the same and different individuals according to the least point-to-point distance on the entire facial surface, for a total of 50 matches and 50 mismatches. RMS value (root mean square) of point-to-point distance between the two models was then calculated through the VAM® software. Intra- and inter-observer errors were assessed through calculation of relative technical error of measurement (rTEM). Possible statistically significant differences between matches and mismatches were assessed through Mann–Whitney test (p < 0.05). Both for intra- and inter-observer repeatability rTEM was between 2.2 and 5.2%. Average RMS point-to-point distance was 0.50 ± 0.28 mm in matches, 2.62 ± 0.56 mm in mismatches (p < 0.01). An RMS threshold of 1.50 mm could distinguish matches and mismatches in 100% of cases. This study provides an improvement to existing 3D-3D superimposition methods and confirms the great advantages which may derive to personal identification of the living from 3D facial analysis.

scholarly journals The Necessity of Mobile Phone Technologies for Public Health Surveillance in Benin

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Yaovi M. G. Hounmanou ◽  
Murielle S. S. Agonsanou ◽  
Victorien Dougnon ◽  
Mahougnon H. B. Vodougnon ◽  
Ephraim M. Achoh ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Smart Phone ◽  
Cross Sectional Study ◽  
Health Surveillance ◽  
Medical Professionals ◽  
Surveillance Systems ◽  
Cross Sectional ◽  
The Public ◽  
Phone Calls

A cross-sectional study was conducted in March 2016 to assess the need of mobile phone technologies for health surveillance and interventions in Benin. Questionnaires were administered to 130 individuals comprising 25 medical professionals, 33 veterinarians, and 72 respondents from the public. All respondents possess cell phones and 75%, 84%, and 100% of the public, medical professionals, and veterinarians, respectively, generally use them for medical purposes. 75% of respondents including 68% of medics, 84.8% of veterinarians, and 72.2% of the public acknowledged that the current surveillance systems are ineffective and do not capture and share real-time information. More than 92% of the all respondents confirmed that mobile phones have the potential to improve health surveillance in the country. All respondents reported adhering to a nascent project of mobile phone-based health surveillance and confirmed that there is no existing similar approach in the country. The most preferred methods by all respondents for effective implementation of such platform are phone calls (96.92%) followed by SMS (49.23%) and smart phone digital forms (41.53%). This study revealed urgent needs of mobile phone technologies for health surveillance and interventions in Benin for real-time surveillance and efficient disease prevention.

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