scholarly journals Evaluating the Performance of Eigenface, Fisherface, and Local Binary Pattern Histogram-Based Facial Recognition Methods under Various Weather Conditions

Technologies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 31
Author(s):  
Md Manjurul Ahsan ◽  
Yueqing Li ◽  
Jing Zhang ◽  
Md Tanvir Ahad ◽  
Kishor Datta Gupta
Keyword(s):  
Time Complexity ◽  
Local Binary Pattern ◽  
Facial Recognition ◽  
Weather Conditions ◽  
The Other ◽  
The Past ◽  
Face Images ◽  
Significant Difference ◽  
Face Datasets ◽  
Pattern Histogram

Facial recognition (FR) in unconstrained weather is still challenging and surprisingly ignored by many researchers and practitioners over the past few decades. Therefore, this paper aims to evaluate the performance of three existing popular facial recognition methods considering different weather conditions. As a result, a new face dataset (Lamar University database (LUDB)) was developed that contains face images captured under various weather conditions such as foggy, cloudy, rainy, and sunny. Three very popular FR methods—Eigenface (EF), Fisherface (FF), and Local binary pattern histogram (LBPH)—were evaluated considering two other face datasets, AT&T and 5_Celebrity, along with LUDB in term of accuracy, precision, recall, and F1 score with 95% confidence interval (CI). Computational results show a significant difference among the three FR techniques in terms of overall time complexity and accuracy. LBPH outperforms the other two FR algorithms on both LUDB and 5_Celebrity datasets by achieving 40% and 95% accuracy, respectively. On the other hand, with minimum execution time of 1.37, 1.37, and 1.44 s per image on AT&T,5_Celebrity, and LUDB, respectively, Fisherface achieved the best result.

scholarly journals The Interaction between Leaf Allelopathy and Symbiosis with Rhizobium of Ulex europaeus on Hawaii Island

Plants ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 226
Author(s):  
Mika Hozawa ◽  
Eiji Nawata
Keyword(s):  
Linear Model ◽  
T Test ◽  
The Other ◽  
Symbiotic Relationship ◽  
Nitrogen Fixing ◽  
Ulex Europaeus ◽  
The Past ◽  
Lettuce Seeds ◽  
Significant Difference ◽  
Hawaii Island

The objective of this study was to assess the magnitudes of the leaf allelopathy of Ulex europaeus in two different habitats, and discuss the driver of the differences, including rhizobia. The magnitudes of leaf allelopathy of the samples collected in two different habitats were assessed by comparing the hypocotyl and radicle lengths of the lettuce seeds tested on the samples. One habitat was in and adjacent to an Acasia koa forest, while the other was more than 50 m away. A. koa is indigenous to Hawaii and known to have a close symbiotic relationship with Bradyrhizobium for nitrogen-fixing. Within the past three years, U. europaeus has newly invaded both sampling sites, whereas the A. koa forest has been there for several decades. The combined result of both hypocotyl and radicle lengths of the lettuce seeds tested on both sites by linear model and multicomparison analyses showed no significant difference. But the radicle lengths of the lettuce seeds tested on U. europaeus sampled in and adjacent to the A. koa forest were significantly longer than those of the samples more than 50 m away, as measured by t-test (p = 0.05). This result suggested that the magnitude of the leaf allelopathy of U. europaeus depended on the distance of the habitat from the A. koa forest.

scholarly journals Face Recognition in an Unconstrained and Real-Time Environment Using Novel BMC-LBPH Methods Incorporates with DJI Vision Sensor

2020 ◽  
Vol 9 (4) ◽  
pp. 54
Author(s):  
Md Manjurul Ahsan ◽  
Yueqing Li ◽  
Jing Zhang ◽  
Md Tanvir Ahad ◽  
Munshi Md. Shafwat Yazdan
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Local Binary Pattern ◽  
Computation Time ◽  
Threshold Value ◽  
Light Illumination ◽  
Rainy Weather ◽  
Face Datasets ◽  
Bad Weather ◽  
Pattern Histogram

Face recognition (FR) in an unconstrained environment, such as low light, illumination variations, and bad weather is very challenging and still needs intensive further study. Previously, numerous experiments on FR in an unconstrained environment have been assessed using Eigenface, Fisherface, and Local binary pattern histogram (LBPH) algorithms. The result indicates that LBPH FR is the optimal one compared to others due to its robustness in various lighting conditions. However, no specific experiment has been conducted to identify the best setting of four parameters of LBPH, radius, neighbors, grid, and the threshold value, for FR techniques in terms of accuracy and computation time. Additionally, the overall performance of LBPH in the unconstrained environments are usually underestimated. Therefore, in this work, an in-depth experiment is carried out to evaluate the four LBPH parameters using two face datasets: Lamar University data base (LUDB) and 5_celebrity dataset, and a novel Bilateral Median Convolution-Local binary pattern histogram (BMC-LBPH) method was proposed and examined in real-time in rainy weather using an unmanned aerial vehicle (UAV) incorporates with 4 vision sensors. The experimental results showed that the proposed BMC-LBPH FR techniques outperformed the traditional LBPH methods by achieving the accuracy of 65%, 98%, and 78% in 5_celebrity dataset, LU dataset, and rainy weather, respectively. Ultimately, the proposed method provides a promising solution for facial recognition using UAV.

Mycotoxin Contamination in Stored Maize and Groundnuts Based on Storage Practices and Conditions in Subhumid Tropical Africa: The Case of Kilosa District, Tanzania

2016 ◽  
Vol 79 (12) ◽  
pp. 2160-2166 ◽  
Author(s):  
K. S. MAGEMBE ◽  
M. W. MWATAWALA ◽  
D. P. MAMIRO
Keyword(s):  
Fumonisin B1 ◽  
Weather Conditions ◽  
Storage Conditions ◽  
The Other ◽  
High Concentration ◽  
Data Loggers ◽  
Honestly Significant Difference ◽  
Significant Difference ◽  
Using Data ◽  
Log Linear

ABSTRACTExperiments were conducted to assess the influence of storage practices on mycotoxin incidences in stored maize and groundnuts in Kilosa District, Eastern Central Tanzania. Factorial experiments were used to test the effects of processing, storage conditions, and protectants at 3-month intervals for 12 weeks. Temperature and relative humidity data were recorded by using data loggers. The differences among the treatment means were compared using Tukey's honestly significant difference test at 5% probability level. The log-linear model was used to determine the influence of weather on mycotoxin. Dried neem (Azadirachta indica) leaves significantly reduced fumonisin B1 (FB1) in stored maize. Levels of FB1 were significantly higher in maize heaped on the floor than in the other tested storage methods (P < 0.001). Similarly, aflatoxin levels were significantly higher in groundnuts stored in nylon bags than in the other tested methods (P < 0.001). The high concentration of mycotoxins at the study villages suggests that storage practices and weather conditions play major roles in mycotoxin production.

scholarly journals Lecturer Attendance System using Face Recognition Application an Android-Based

2021 ◽  
Vol 3 (2) ◽  
pp. 167-173
Author(s):  
Feri Susanto ◽  
Fauziah Fauziah ◽  
Andrianingsih Andrianingsih
Keyword(s):  
Face Recognition ◽  
Local Binary Pattern ◽  
Facial Recognition ◽  
Recognition System ◽  
Security Systems ◽  
Technological Advances ◽  
Face Recognition System ◽  
The Face ◽  
Operational Activities ◽  
Pattern Histogram

In the field of industries, businesses, and offices the use of security systems and administrative management through data input using a face recognition system is being developed. Following the era of technological advances, communication and information systems are widely used in various administrative operational activities and company security systems because it is assessed by using a system that is based on facial recognition security levels and more secure data accuracy, the use of such systems is considered to have its characteristics so it is very difficult for other parties to be able to engineer and manipulate data produced as a tool to support the company's decision. Related to this, causing the author is to try to research the detection of facial recognition that is present in the application system through an Android device, then face recognition detection will be connected. and saved to the database that will be used as data about the presence of teaching lecturers. Using the local binary pattern histogram algorithm method to measure the face recognition system that can be applied as a technique in the attendance system of lecturers to be more effective and efficient. Based on testing by analyzing the false rate error rate and the false refusal rate can be seen that the average level of local binary pattern histogram accuracy reaches 95.71% better than through the Eigenface method which is equal to 76.28%.

scholarly journals Employee Attendance Management System using Face Recognition

2021 ◽  
Vol 9 (VI) ◽  
pp. 5303-5308
Author(s):  
P. Vyshnavi
Keyword(s):  
Work Environment ◽  
Local Binary Pattern ◽  
Facial Recognition ◽  
Tracking System ◽  
Health And Safety ◽  
Identification System ◽  
Facial Features ◽  
Automated Identification ◽  
Employee Attendance ◽  
Pattern Histogram

Automatic Facial Recognition Attendance System is a type of automated identification system that can recognize any person whose facial features have been saved in the database. This technology could be used by all corporations in the coming years, offices to keep track of who comes and goes. The attendance method is based on facial recognition technology. A real-time, contactless attendance tracking system that is extremely useful in today's world circumstances of a pandemic. After COVID, the work environment will not be the same. Despite the fact that the virus is still spreading, firms are attempting to restore on-premise operations in order to assure business continuity. Employees' health and safety are of utmost importance in such situations. Organizations are looking for methods to provide employees with a COVID-free workspace, and a touchless check-in is the first step. The attendance system uses a set of techniques like Haarcascade classifier and Local Binary Pattern Histogram(LBPH) Face Recognizer in deep learning to detect people in front of the camera and then changes their attendance in the attendance sheet automatically.

scholarly journals Influence of meteorological factors on the onset of primary spontaneous pneumothorax

2018 ◽  
Vol 100 (8) ◽  
pp. 606-611 ◽  
Author(s):  
Y Aljehani ◽  
R Niaz ◽  
F Almajid ◽  
H Elbawab
Keyword(s):  
Atmospheric Pressure ◽  
Pressure Difference ◽  
Spontaneous Pneumothorax ◽  
Meteorological Parameters ◽  
Meteorological Factors ◽  
Weather Conditions ◽  
Primary Spontaneous Pneumothorax ◽  
The Other ◽  
Average Temperature ◽  
Significant Difference

Introduction Although links between meteorological conditions and primary spontaneous pneumothorax have been proposed, the reports are controversial. The aim of the study is to correlate between climatic changes and the development of this condition. Materials and methods A retrospective chart review included all patient presenting with primary spontaneous pneumothorax to King Fahd Hospital, Imam Abdulrahman Bin Faisal University, Alkhobar, Saudi Arabia, from 1 January 2005 to 31 December 2016. Meteorological data were collected from King Abdulaziz airbase station using an online source for the same time interval. The data were analysed to determine differences in weather conditions between days on which primary spontaneous pneumothorax occurred and those in which it did not. Logistic regression model was used to obtain predicted risks for the onset of primary spontaneous pneumothorax with respect to weather conditions. Result Two hundred and eighty-nine patients were found to have primary spontaneous pneumothorax in the 281 days included in the study. Among the meteorological parameters, significant differences were found in average temperature and atmospheric pressure difference between day of admission and two days before the admission, between days with primary spontaneous pneumothorax and days without. There was no significant difference in the other meteorological factors between days with primary spontaneous pneumothorax and days without. Conclusion Two hundred and eighty-nine patients were found to have primary spontaneous pneumothorax in the 281 days included in the study. Among the meteorological parameters, significant differences were found in average temperature and atmospheric pressure difference between day of admission and two days before the admission, between days with primary spontaneous pneumothorax and days without. There was no significant difference in the other meteorological factors between days with primary spontaneous pneumothorax and days without.

scholarly journals Correlation between climate data and land altitude for Fasciola hepatica infection in cattle in Santa Catarina, Brazil

2020 ◽  
Vol 29 (3) ◽  
Author(s):  
Ana Elisa Pereira Silva ◽  
Corina da Costa Freitas ◽  
Luciano Vieira Dutra ◽  
Marcelo Beltrão Molento
Keyword(s):  
Fasciola Hepatica ◽  
Clinical Importance ◽  
Weather Conditions ◽  
Climate Data ◽  
Santa Catarina ◽  
Climate Conditions ◽  
The Past ◽  
Food Borne ◽  
Significant Difference

Abstract Fascioliasis is a food-borne parasitic disease that affects a range of animals, including humans caused by Fasciola hepatica. The present study aimed to determine the spatial distribution of bovine fasciolosis and to assess the correlation between the high Positivity Index (PI) and climate data and land altitude, from 2004 to 2008 and 2010 in Santa Catarina (SC), Brazil. Condemned livers of slaughtered animals were obtained from 198 out of 293 municipalities and from 518.635 animals, exclusively from SC. There was a statistically significant difference (P < 0.001) between the prevalence of F. hepatica and land altitude ( ρ ^ s = -0.43). The highest PI (above 10.1%) was observed in cities at 500 to 600 m (P < 0.01; ρ ^ s = -0.47) of altitude. There was no correlation between fascioliasis and rainfall in SC. It was determined that weather conditions in the past decade did not impose any limitation to the occurrence of the parasite, making it a disease of permanent clinical importance. These findings are essential to regions with similar geographical and climate conditions (i.e. altitude), when considering long-term control measurements, where animals and humans can be infected.

scholarly journals Vocab SIG: Re-examining semantic clustering: Insight from memory models

2014 ◽  
Vol 38 (5) ◽  
pp. 27
Author(s):  
Tomoko Ishii
Keyword(s):  
Working Memory ◽  
Past Research ◽  
Memory Models ◽  
The Other ◽  
Visual Features ◽  
Semantic Clustering ◽  
Visual Component ◽  
The Past ◽  
Significant Difference ◽  
Different Types

It has been repeatedly argued that semantically related words should not be learned together because the learning is impeded. However, the results of past research are not all in agreement, with some providing favorable results for semantic clustering, and some seeming to suggest different types of similarity affect memory in different ways. The types of connections that truly cause the problem therefore need to be discussed more carefully. Focusing on a visual component, which is commonly observed across different models of working memory, a study was conducted to examine if learners have difficulty memorizing a group of words that describe items with a common physical feature. The study compared the learning of three types of word sets: unrelated, semantically related, and physically related. While no statistically significant difference was observed between semantically related and unrelated sets, the scores for physically related sets were significantly lower than those for the other two types. This suggests the possibility that the impeding effect of semantic clustering reported in the past could be partly due to the nature of semantically similar words, which sometimes share visual features. 「意味的に関連のある語を同時に学習すると記憶の妨げになる」という考え方が（語彙習得研究者の間に）繰り返し論じられている。しかし、先行研究の中には逆の結果を示すものや、意味上の関連性が異なると学習効果が異なることを示すものもあり、記憶の妨げになる要因が何であるのかは、慎重な検証が求められる。本論は、心理学におけるワーキングメモリーの研究において視覚イメージが重要視されていることに着目し、「関連のない語群」「意味的に関連のある語群」「形状の似ている物を指す語群」の記憶の効率性を検証したものである。その結果、「意味的に関連のある語群」と「関連のない語群」は統計的に有意差が見られなかったが、「形状の似ている物を指す語群」が他の語群よりも記憶しにくいことが示された。「意味的に関連する語は記憶しにくい」と言われているのは実は、意味的に関連する語は形状の似ているものを指すことがしばしばあるからではないか、という可能性が示された。

scholarly journals Facial Recognition Technique with Combination Method of Local Binary Pattern Histogram and Image Euclidean Distance

2019 ◽  
Vol 1196 ◽  
pp. 012009
Author(s):  
Erwin ◽  
Saparudin ◽  
M. Fachrurrozi ◽  
Alvin Tamaarsa ◽  
Andy Zhang
Keyword(s):  
Euclidean Distance ◽  
Local Binary Pattern ◽  
Facial Recognition ◽  
Combination Method ◽  
Image Euclidean Distance ◽  
Recognition Technique ◽  
Pattern Histogram

scholarly journals Video Based Facial Detection & Recognition

2019 ◽  
Vol 8 (9) ◽  
pp. 661-665
Keyword(s):  
Local Binary Pattern ◽  
Facial Recognition ◽  
Pattern Histogram

The identification of a person through images has been on cards for a long while but identification/recognition through video is not so common that is what we have tried to explain by the use of some classifiers like HAAR, Local Binary Pattern (LBP) and Local Binary Pattern Histogram (LBPH). These all classifiers are used for facial detection & recognition respectively. For the Facial Detection, HAAR Classifier is used while for Facial Recognition Local Binary Pattern Histogram is used.

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