scholarly journals Color detection algorithm for early fire diagnostics

2021 ◽  
Vol 2131 (2) ◽  
pp. 022123
Author(s):  
E N Ostroukh ◽  
M V Privalov ◽  
S D Markin
Keyword(s):  
Noise Suppression ◽  
Visible Spectrum ◽  
Detection Algorithm ◽  
Video Streams ◽  
Problem Domain ◽  
Detection Approach ◽  
Color Detection ◽  
Different Color ◽  
Selection Of ◽  
Color Components

Abstract In the paper as a problem domain was chosen oil mining and its peculiarities related to early fire diagnostics. Main feature of the described method of early fire diagnostics is application of color detection algorithm together with video sequence acquired from survey cameras. Drawback of the known algorithms of fire diagnostics that also use video streams is selection of the only one color of visible spectrum. Proposed algorithm makes frames preprocessing with purpose of white noise and Gaussian noise suppression. Main feature is complex registration of color components of fire images that are specific to chosen problem domain. Described obtained results of practical application of proposed color detection approach. Experiments were carried out using test video sequences from Bilkent University and Dyntex database. It is shown that advantage of the proposed approach is an ability to select different color components and process them in complex during color detection.

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas

2011 ◽  
Vol 59 (2) ◽  
pp. 137-140 ◽  
Author(s):  
S. Szczepański ◽  
M. Wöjcikowski ◽  
B. Pankiewicz ◽  
M. KŁosowski ◽  
R. Żaglewski
Keyword(s):  
Urban Areas ◽  
Traffic Monitoring ◽  
Detection Algorithm ◽  
Frame Rate ◽  
Integrated Sensor ◽  
The Road ◽  
Moving Vehicles ◽  
Direction Of Movement ◽  
Account Due ◽  
Selection Of

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas This paper describes the idea and the implementation of the image detection algorithm, that can be used in integrated sensor networks for environment and traffic monitoring in urban areas. The algorithm is dedicated to the extraction of moving vehicles from real-time camera images for the evaluation of traffic parameters, such as the number of vehicles, their direction of movement and their approximate speed. The authors, apart from the careful selection of particular steps of the algorithm towards hardware implementation, also proposed novel improvements, resulting in increasing the robustness and the efficiency. A single, stationary, monochrome camera is used, simple shadow and highlight elimination is performed. The occlusions are not taken into account, due to placing the camera at a location high above the road. The algorithm is designed and implemented in pipelined hardware, therefore high frame-rate efficiency has been achieved. The algorithm has been implemented and tested in FPGA and ASIC.

SELECTION OF CONTROLLABLE PARAMETERS OF THE BINARY DATA ARRAY DETECTION ALGORITHM IN THE INTEGRATED MANAGEMENT SYSTEM

2021 ◽  
Vol 4 (3) ◽  
pp. 11-18
Author(s):  
Khakimjon Zaynidinov ◽  
◽  
Odilbek Askaraliyev
Keyword(s):  
Management System ◽  
Binary Data ◽  
Integrated Management ◽  
Research Work ◽  
Hash Functions ◽  
Experimental Tests ◽  
Detection Algorithm ◽  
Identification Algorithm ◽  
Solution Algorithms ◽  
Selection Of

The article discusses the selection of parameters for the algorithm for determining binary data arrays included in the control system, developed by the authors using independent substitution methods. Based on the analysis of the algorithms of non-cryptographic hash functions, the hash function based on the linear matching method was selected as the basis for independent substitution methods. Simplified schemes of algorithms developed for creating and comparing identifiers using a set of basic hash functions are given. An array of binary data was selected and based on the appropriate values for the size of the divisible blocks and the number of basic hashfunctions used for independent substitutions. The selection of binary data arrays in information systems integrated into the management system was done for the purpose of intellectual processing of incoming data. The properties of the array of data entering integrated systems are studied. The authors conducted experimental tests in the selected direction and presented the results of similarity assessment measurements for various parameters of the identification algorithm. In addition, the article conductedexperiments on the object of study using the selected mathematical model, based on the analytical conclusions. Initiator elements are studied and analyzed using a set of hash functions. An algorithm for comparison of selected identifiers has been developed. A generation algorithm has been developed to demonstrate and test the proposed solution. Algorithms based on analysis and experiments, and methods for selecting binary data arrays using the ash function have been experimentally tested. Based on the results, the indicators are shown. Based on the results obtained, the analytical conclusions and problem solutions of the research work were recognized

scholarly journals Response of Polycrystalline Solar Cell Outputs to Visible Spectrum and other Light Sources-a Case Study

2018 ◽  
Vol 8 (6) ◽  
pp. 4096
Author(s):  
Ayman Y. Al-Rawashdeh ◽  
Omar Albarbarawi ◽  
Ghazi Qaryouti
Keyword(s):  
Solar Cells ◽  
Visible Spectrum ◽  
Artificial Light ◽  
Light Sources ◽  
Variable Response ◽  
Artificial Illumination ◽  
Different Color ◽  
Color Filters ◽  
Sunlight Radiation

<p>In this case study, two polycrystalline solar modules were installed outdoors (irradiated by sunlight) and indoors (irradiated by artificial lights). The solar cells in both cases were installed using different color filters that allowed the passage of certain light frequencies. The amount of energy produced by each module were measured and compared to a reference module with no filter. The results indicated the variable response of polycrystalline solar cells to natural and artificial light sources, being more responsive in both cases to red band color as could be deduced from their % current outputs (72.5% sunlight radiation; 84.38% artificial light sources). Other colors, including yellow, green, orange and violet afforded acceptable outputs. The results indicated that electrical outputs of indoor solar cells decreased when colored filters were used, but red filter in general afforded the maximum outputs, for both the artificially radiated indoor and naturally radiated outdoor solar cells. The case study suggests the possible complementary advantage of using indoor mounted solar cells for the production of electricity during artificial illumination period of the day.</p>

scholarly journals Ultraviolet vision in larval Neogonodactylus oerstedii

2022 ◽  
Author(s):  
Marisa S. McDonald ◽  
Sitara Palecanda ◽  
Jonathan H. Cohen ◽  
Megan L. Porter
Keyword(s):  
Visual Pigment ◽  
Molecular Diversity ◽  
Animal Kingdom ◽  
Uv Sensitivity ◽  
Color Detection ◽  
Uv Vision ◽  
Ultraviolet Vision ◽  
The Caribbean ◽  
Different Color ◽  
Spectral Channels

Stomatopod crustaceans have among the most complex eyes in the animal kingdom, with up to twelve different color detection channels. The capabilities of these unique eyes include photoreception of ultraviolet (UV) wavelengths (&lt;400 nm). UV vision has been well characterized in adult stomatopods but has not been previously demonstrated in the comparatively simpler larval eye. Larval stomatopod eyes are developmentally distinct from their adult counterpart and have been described as lacking the visual pigment diversity and morphological specializations found in adult eyes. However, recent studies have provided evidence that larval stomatopod eyes are more complex than previously thought and warrant closer investigation. Using electroretinogram recordings in live animals we found physiological evidence of blue and UV sensitive photoreceptors in larvae of the Caribbean stomatopod species Neogonodactylus oerstedii. Transcriptomes of individual larvae were used to identify the expression of three distinct UV opsins transcripts, which may indicate the presence of multiple UV spectral channels. This is the first paper to document UV vision in any larval stomatopod, expanding our understanding of the importance of UV sensitivity in plankton. Similar to adults, larval stomatopod eyes are more complex than expected and contain previously uncharacterized molecular diversity and physiological functions.

scholarly journals Natural Feature Detection on Mobile Phones with 3D FAST

2010 ◽  
Vol 9 (4) ◽  
pp. 29-34 ◽  
Author(s):  
Achim Weimert ◽  
Xueting Tan ◽  
Xubo Yang
Keyword(s):  
Feature Detection ◽  
Feature Matching ◽  
Hessian Matrix ◽  
Detection Algorithm ◽  
Scale Invariant ◽  
Natural Feature ◽  
Detection Approach ◽  
Scale Levels ◽  
Speed Up ◽  
Low Performance

In this paper, we present a novel feature detection approach designed for mobile devices, showing optimized solutions for both detection and description. It is based on FAST (Features from Accelerated Segment Test) and named 3D FAST. Being robust, scale-invariant and easy to compute, it is a candidate for augmented reality (AR) applications running on low performance platforms. Using simple calculations and machine learning, FAST is a feature detection algorithm known to be efficient but not very robust in addition to its lack of scale information. Our approach relies on gradient images calculated for different scale levels on which a modified9 FAST algorithm operates to obtain the values of the corner response function. We combine the detection with an adapted version of SURF (Speed Up Robust Features) descriptors, providing a system with all means to implement feature matching and object detection. Experimental evaluation on a Symbian OS device using a standard image set and comparison with SURF using Hessian matrix-based detector is included in this paper, showing improvements in speed (compared to SURF) and robustness (compared to FAST)

Can intubation be improved with endotracheal tubes marked with a color scale? Randomized controlled study.

2021 ◽  
Author(s):  
Juan Pablo Berazategui ◽  
Ramon Pio Larcade ◽  
Nestor Vain ◽  
Adriana Andrea Castro ◽  
Rose Mari Soria ◽  
...  
Keyword(s):  
Controlled Study ◽  
Endotracheal Tubes ◽  
Correct Placement ◽  
Randomized Controlled ◽  
Color Scale ◽  
Clinical Scenarios ◽  
Significant Difference ◽  
Different Color ◽  
Time Required ◽  
Selection Of

Objective: To assess if a color scale in the endotracheal tube (ETT) helps operators to correctly select the size and depth of placement of the ETT and decrease the time required, compared with the usual numeric ETT scale, in a mannequin model. Design/Methods: The study was conducted in 8 centers. Each size of the ETT was identified with different color by size. All experimental ETT had two painted zones: the mouthpiece and an area of 1 cm marked with the same color (to identify where the ETT should be taped above the lip). The operators were trained as part of the protocol using a video. Four clinical scenarios requiring endotracheal intubation were designed and randomly assigned. Each operator had to select the size and depth of ETT based on the BW, and then had to perform 4 intubation procedures. Results: 108 operators performed 432 intubations. No difference were found in the correct placement and selection of the ETT. Median time (in seconds) required for intubation using numeric vs. experimental tube was: for ETT Ø 2.5, 11.5 vs. 8 (p<0.001), ETTØ3,12 vs. 10 (p<0.001), ETT Ø 3.5, 15.5 vs.12 (p 0.003), ETT Ø4 12 vs.11 (p 0.019). Conclusions: No significant difference was observed in the selection and correct placement of the ETT. However, the intubation time was significantly shorter using the experimental ETT. This device could improve the effectiveness of intubation by reducing the time needed to properly place the ETT at mid trachea.

scholarly journals A Deep Learning-Based Fragment Detection Approach for the Arena Fragmentation Test

2020 ◽  
Vol 10 (14) ◽  
pp. 4744
Author(s):  
Hyukzae Lee ◽  
Jonghee Kim ◽  
Chanho Jung ◽  
Yongchan Park ◽  
Woong Park ◽  
...  
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Object Detection ◽  
High Speed ◽  
Detection Algorithm ◽  
Learning Technologies ◽  
Experimental Conditions ◽  
Fragmentation Test ◽  
Detection Approach ◽  
Previous Image

The arena fragmentation test (AFT) is one of the tests used to design an effective warhead. Conventionally, complex and expensive measuring equipment is used for testing a warhead and measuring important factors such as the size, velocity, and the spatial distribution of fragments where the fragments penetrate steel target plates. In this paper, instead of using specific sensors and equipment, we proposed the use of a deep learning-based object detection algorithm to detect fragments in the AFT. To this end, we acquired many high-speed videos and built an AFT image dataset with bounding boxes of warhead fragments. Our method fine-tuned an existing object detection network named the Faster R-convolutional neural network (CNN) on this dataset with modification of the network’s anchor boxes. We also employed a novel temporal filtering method, which was demonstrated as an effective non-fragment filtering scheme in our recent previous image processing-based fragment detection approach, to capture only the first penetrating fragments from all detected fragments. We showed that the performance of the proposed method was comparable to that of a sensor-based system under the same experimental conditions. We also demonstrated that the use of deep learning technologies in the task of AFT significantly enhanced the performance via a quantitative comparison between our proposed method and our recent previous image processing-based method. In other words, our proposed method outperformed the previous image processing-based method. The proposed method produced outstanding results in terms of finding the exact fragment positions.

scholarly journals Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic

2019 ◽  
Vol 11 (19) ◽  
pp. 2200 ◽  
Author(s):  
Léo Edel ◽  
Jean-François Rysman ◽  
Chantal Claud ◽  
Cyril Palerme ◽  
Christophe Genthon
Keyword(s):  
Detection Algorithm ◽  
The Arctic ◽  
Mountainous Areas ◽  
Phase Precipitation ◽  
Water Path ◽  
Brightness Temperatures ◽  
Microwave Humidity Sounder ◽  
Snow Water ◽  
Potential Use ◽  
Selection Of

This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m−2 and 50% of the weak snowfall rate events (snow water path ≤50 g m−2. The brightness temperatures at 190.3 GHz and 183.3 ± 3 GHz, the integrated water vapor, and the temperature at 2 m are identified as the most important variables for snowfall detection. The algorithm tends to underestimate the snowfall occurrence over Greenland and mountainous areas (by as much as −30%), likely due to the dryness of these areas, and to overestimate the snowfall occurrence over the northern part of the Atlantic (by up to 30%), likely due to the occurrence of mixed phase precipitation. An interpretation of the selection of the variables and their importance provides a better understanding of the snowfall detection algorithm. This work lays the foundation for the development of a snowfall rate quantification algorithm.

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