Mobile document analysis technologies became widespread and important, and growing reliance on the performance of critical processes, such as identity document data extraction and verification, lead to increasing spee...
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ISBN:
(纸本)9783030863319
Mobile document analysis technologies became widespread and important, and growing reliance on the performance of critical processes, such as identity document data extraction and verification, lead to increasing speed and accuracy requirements. Camera-based documents recognition on mobile devices using video stream allows to achieve higher accuracy, however in real time systems the actual time of individual imageprocessing needs to be taken into account, which it rarely is in the works on this subject. In this paper, a model of real-time document recognition system is described, and three frame processing strategies are evaluated, each consisting of a per-frame recognition results combination method and a dynamic stopping rule. The experimental evaluation shows that while full combination of all input results is preferable if the frame recognition time is comparable with frame acquisition time, the selection of one best frame based on an input quality predictor, or a combination of several best frames, with the corresponding stopping rule, allows to achieve higher mean recognition results accuracy if the cost of recognizing a frame is significantly higher than skipping it.
The enterprises digitalization determines the development trends of the industrial sector. There is a need to reduce the percent of human participation in processes associated with conveyor production, which requires ...
The enterprises digitalization determines the development trends of the industrial sector. There is a need to reduce the percent of human participation in processes associated with conveyor production, which requires the high-tech solutions integration. Due to the lack of quality control on the assembly line, enterprises produce a large percentage of defective products. The article discusses a possible solution to the problem of imageprocessing for monitoring defects in products moving along a conveyor belt. The use of neural network technologies allows us to identify defects in production in real time, and the use of a robotic arm allows us to immediately remove such products from the assembly line. As a result of the research, it is planned to implement a software and hardware complex of a robotic manipulator using computer vision technologies that can distinguish objects and mechanically influence them.
Crossing the road is one of the major problems, due to the increase of fast-moving vehicles on the road. The challenges in the existing techniques utilized for traffic control can be overcome by using the Smart Traffi...
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ISBN:
(纸本)9781665489638
Crossing the road is one of the major problems, due to the increase of fast-moving vehicles on the road. The challenges in the existing techniques utilized for traffic control can be overcome by using the Smart Traffic Light Control System using imageprocessing, proposed in this paper and allowing pedestrians to walk on busy roads conveniently. It is found that the Canny Edge Detection Technique is a very effective method among the various edge detection algorithms. The suggested method reduces the waiting time in zebra crossing by immediately controlling the traffic light and gives more time for elderly and handicapped pedestrians to cross the roads safely even during heavy traffic. When compared to all the traditional techniques, imageprocessing is an efficient method for traffic control. This technique removes the usage of unwanted hardware like sensors which are used to sense noises. This prevents the wastage of time for vehicles which is more essential for emergency vehicles. The output of the code is obtained by image matching. The results are shown in three scenarios: less traffic, moderate traffic, and more traffic.
Hyperspectral image analysis is one of the most important topics in the field of remote sensing. As the band dimension of hyperspectral image increases, it may cause a curse of dimensionality. Band selection could cho...
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ISBN:
(纸本)9781665426053
Hyperspectral image analysis is one of the most important topics in the field of remote sensing. As the band dimension of hyperspectral image increases, it may cause a curse of dimensionality. Band selection could choose a subset of bands that is the most effective for classification recognition to achieve dimensionality reduction. Furthermore, binary coding is more suitable for solving the band selection problem. Therefore, a band selection method for hyperspectral image based on binary coded hybrid rice optimization algorithm is proposed in the paper. The band selection problem is solved as a combinatorial optimization problem by defining an objective function based on the classification accuracy and the number of bands. The proposed method is compared with other nature-inspired algorithms on Indian Pines, Salinas, Kennedy Space Center, and Pavia University hyperspectral datasets. Experimental results demonstrate that the proposed method achieves satisfactory results in terms of performance and execution time for band selection.
Nowadays, amount of usage of banking server is increasing due to increase in number of account holder in the bank. Therefore securing the bank server is the biggest challenge for researchers and algorithm developers. ...
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The detection and tracking of cars is a significant and useful aspect of traffic surveillance systems, which is essential for the efficient management of traffic and the security of drivers and passengers. The primary...
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In this article implementation process of the camera from the integrated field-programmable gate array or FPGA for problems of identification of the vehicles used on the automated points of weight and dimensional cont...
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ISBN:
(纸本)9781665400756
In this article implementation process of the camera from the integrated field-programmable gate array or FPGA for problems of identification of the vehicles used on the automated points of weight and dimensional control by search of edges of the object in the detector Sobelya method is considered. In development process in the verilog language the main parts of interaction of the camera with the personal computer, for carrying out binarization of the image and also for its frequency filtering were described. The Fourier transform involves a large number of operations, which requires a large amount of computing power. To get around this limitation, the article discusses fast Fourier transform algorithms.
Shape recognition in images represents one of the complex and hard-solving problems in computer vision due to its nonlinear, stochastic and incomplete nature. Classical imageprocessing techniques have been normally u...
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Shape recognition in images represents one of the complex and hard-solving problems in computer vision due to its nonlinear, stochastic and incomplete nature. Classical imageprocessing techniques have been normally used to solve this problem. Alternatively, shape recognition has also been conducted through metaheuristic algorithms. They have demonstrated to have a competitive performance in terms of robustness and accuracy. However, all of these schemes use old metaheuristic algorithms as the basis to identify geometrical structures in images. Original metaheuristic approaches experiment several limitations such as premature convergence and low diversity. Through the introduction of new models and evolutionary operators, recent metaheuristic methods have addressed these difficulties providing in general better results. This paper presents a comparative analysis on the application of five recent metaheuristic schemes to the shape recognition problem such as the Grey Wolf Optimizer (GWO), Whale Optimizer Algorithm (WOA), Crow Search Algorithm (CSA), Gravitational Search Algorithm (GSA) and Cuckoo Search (CS). Since such approaches have been successful in several new applications, the objective is to determine their efficiency when they face a complex problem such as shape detection. Numerical simulations, performed on a set of experiments composed of images With different difficulty levels, demonstrates the capacities of each approach. (C) 2020 The Authors. Published by Atlantis Press B.v.
The requirement of imageprocessing is very much required on the present world. Almost in every field it has a huge application. Detecting and recognizing the face is one of the most trending imageprocessingsystems ...
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Roads are the most commonly used mode of transportation. However, due to the frequent use of roads, it requires an organized assistance. Manually screening the potholes or damaged patches is highly impossible and inac...
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ISBN:
(纸本)9781665489638
Roads are the most commonly used mode of transportation. However, due to the frequent use of roads, it requires an organized assistance. Manually screening the potholes or damaged patches is highly impossible and inaccurate. This research work investigates the detection of potholes or patches by using a camera. imageprocessing models are used to detect the potholes or patches. The proposed system has been evaluated in a Desktop environment by using the Open Cv library. To perform this task, a smart imageprocessing model with Hough transform are used.
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