scholarly journals An Algorithm of Occlusion Detection for the Surveillance Camera

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Peng Shi ◽  
Bin Hou ◽  
Jing Chen ◽  
Yunxiao Zu
Keyword(s):  
Window Size ◽  
Local Binary Patterns ◽  
Combination Method ◽  
Practical Significance ◽  
Reference Image ◽  
Surveillance Camera ◽  
Frame Difference ◽  
Background Difference ◽  
Background Image ◽  
The Internet Of Things

As more and more surveillance cameras are deployed in the Internet of Things, it takes more and more work to ensure the cameras are not occluded. An algorithm of detecting whether the surveillance camera is occluded is proposed by comparing the similarity of the images in this paper. Firstly, the background modeling method based on frame difference is improved. The combination method of the background difference and frame difference is proposed, and the experimental results showed that the combination algorithm can extract the background image of the video more quickly and accurately. Secondly, the LBP (Local Binary Patterns) algorithm is used to compare the similarity between the background image and the reference image. By changing the window size of the LBP algorithm and setting an appropriate threshold, the actual demands can be satisfied. So, the algorithms proposed in this paper have high application value and practical significance.

scholarly journals Dynamic Duty-Cycle MAC Protocol for IoT Environments and Wireless Sensor Networks

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4069 ◽  
Author(s):  
Gayoung Kim ◽  
Jin-Gu Kang ◽  
Minjoong Rim
Keyword(s):  
Energy Consumption ◽  
Duty Cycle ◽  
Traffic Congestion ◽  
Mac Protocol ◽  
Window Size ◽  
Transmission Delay ◽  
Contention Window ◽  
Peak Time ◽  
Contention Window Size ◽  
The Internet Of Things

This paper proposes a new protocol that can be used to reduce transmission delay and energy consumption effectively. This will be done by adjusting the duty-cycle (DC) ratio of the receiver node and the contention window size of the sender node according to the traffic congestion for various devices in the Internet of Things (IoT). In the conventional duty-cycle MAC protocol, the data transmission delay latency and unnecessary energy consumption are caused by a high collision rate. This is because the receiver node cannot sufficiently process the data of the transmitting node during the traffic peak time when the transmission and reception have the same duty-cycle ratio. To solve this problem, this paper proposes an algorithm that changes the duty-cycle ratio of the receiver and broadcasts the contention window size of the senders through Early Acknowledgment (E-ACK) at peak time and off/peak time. The proposed algorithm, according to peak and off/peak time, can transmit data with fewer delays and minimizes energy consumption.

Adaptive Moving Vehicle Detection Algorithm Based on Hybrid Background Subtraction and Frame Difference

2014 ◽  
Vol 644-650 ◽  
pp. 930-933 ◽  
Author(s):  
Yan Li Luo ◽  
Han Lin Wan ◽  
Li Xia Xue ◽  
Qing Bin Gao
Keyword(s):  
Background Subtraction ◽  
Vehicle Detection ◽  
Detection Algorithm ◽  
Target Image ◽  
Moving Vehicle ◽  
Frame Difference ◽  
Video Frequency ◽  
Background Difference ◽  
Moving Vehicle Detection ◽  
Initial Target

This paper proposes an adaptive moving vehicle detection algorithm based on hybrid background subtraction and frame difference. The background image of continuous video frequency is reconstructed by calculating the maximun probability grayscale using grey histogram; Moving regions is gained by frame defference, the initial target image is obtained by background difference method,moving regions image and initial target image AND,XOR and OR operations to get the vehicle moving target images. Experimental results show that the algorithm can response timely to the actual scene changes and improve the quality of moving vehicle detection.

No-Reference Image Quality Assessment Using Salient Local Binary Patterns

2018 ◽  
Vol 2018 (12) ◽  
pp. 367-1-367-6
Author(s):  
Pedro Garcia Freitas ◽  
Welington Yorihiko Lima Akamine ◽  
Mylène Christine Queiroz de Farias;
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Local Binary Patterns ◽  
Reference Image

Application of the Internet of Things in Colleges' Management

2014 ◽  
Vol 905 ◽  
pp. 736-741
Author(s):  
Li Na Li ◽  
Peng Fei Zhao
Keyword(s):  
Higher Education ◽  
Internet Of Things ◽  
Practical Significance ◽  
The Internet ◽  
System Function ◽  
Key Technology ◽  
Education Management ◽  
New Information ◽  
Basic Work ◽  
The Internet Of Things

The Internet of things is a new information technology in many fields. This paper focuses on the field of higher education, and puts forward some ideas and application in education management. This paper expounds the application of the Internet of things management system function, structure architecture diagram, the basic work principle and key technology. These contents, to solve practical problems in Colleges management, have certain practical significance.

scholarly journals Particle Swarm Image Matching on Epipolar Line

2014 ◽  
Vol XL-4 ◽  
pp. 87-91
Author(s):  
J.-S. Hsia
Keyword(s):  
Image Matching ◽  
Particle Swarm ◽  
Window Size ◽  
Pso Algorithm ◽  
Least Square ◽  
Image Point ◽  
Reference Image ◽  
Epipolar Line ◽  
Matching Method ◽  
The Difference

This paper presents a method for determining the 3D position of an image point on a reference image using particle swarm optimization (PSO) to search the height (Z value) that gives the biggest Normalized Cross Correlation (NCC) coefficient. The searching area is in the surrounding of the height of the image point. The NCC coefficient evaluates the similarity with the image point and a corresponding point on an epipolar line in the search image. The position of corresponding image point on the epipolar line is determined by the height point on a sloping line locus. The PSO algorithm starts with a swarm of random particles. The position of each particle is a potential solution in the problem space. Each particle is given a randomized velocity and attracted toward the location of the best fitness. The position of each particle is iteratively modified by adding a newly computed velocity to its current position. The velocity is updated by three factors which are two attractions from local best position and global best position, two strengths of the attractions, and two uniform random numbers for each attraction. The iteration will stop when the current solution is convergent. The time of computation is highly related to the range of height and the interval of height enumeration when the approach to find a corresponding image point of an image point on a reference image is based on the height enumeration along sloping line locus. The precision of results can be improved by decreasing the interval of height enumeration. This shows the limitation of the enumeration method in the efficiency and accuracy. The issue is overcome by a method of using PSO algorithm. The proposed method using different parameters such as the size of image window, the number of particles, and the size of the height searching range has been applied to aerial stereo images. The accuracy of tested results is evaluated on the base of the comparison to the reference data from the results of least-square matching being manually given initial points. The evaluation result shows that tested results has given a solution to a level of less than 1 centimetre without using refined image matching method. The same level of accuracy can reach even when the searching range is bigger than 90 meters. But the difference of image window size may lead to the change of the matching result. And, without the procedures of both coarse-to-fine hierarchical solution and refined image matching method, the algorithm still can give the same accuracy level of least-square image matching resulting. This method also shows its ability to give reasonable matching results without manual assistance.

scholarly journals A local binary patterns/variance operator based on guided filtering for seismic fault detection

2021 ◽  
Vol 3 (12) ◽  
Author(s):  
Renfei Tian ◽  
Xue Lei ◽  
Min Ouyang
Keyword(s):  
Fault Detection ◽  
Seismic Data ◽  
Oil And Gas ◽  
Local Binary Patterns ◽  
Identification Accuracy ◽  
Practical Significance ◽  
Noise Interference ◽  
Oil And Gas Exploration ◽  
Seismic Fault ◽  
Guided Filtering

AbstractAiming at suppressing noise interference, improving the fault detection ability of seismic data, fully excavating the effective information in seismic data, and further improving the accuracy of fault detection, this study proposes a seismic fault detection method that combines the local binary pattern/variance (LBP/VAR) operator with guided filtering. The proposed method combines the advantages of LBP/VAR and guided filtering to remove noise from seismic data, and can simultaneously smooth the data and preserve linear features. When compared with several existing methods (coherent operator, LBP/VAR operator, LBP/VAR operator based on median filtering, and Canny operator based on guided filtering), the proposed method exhibits a better SNR, a better ability to identify small faults, and robustness to noise. This novel algorithm can control the balance between noise attenuation and effective signal preservation as well as effectively detect faults in seismic data. Therefore, the proposed method effectively improves the fault identification accuracy, facilitates the gas-bearing analysis of the structure, provides guidance for the actual well location deployment of the project, and has important practical significance for oil and gas exploration and development.

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