Network delays and packet losses are two critical parameters for the performance of networked control systems (NCS) in non-deterministic packet networks, such as the Internet. To avoid the need of a remote location, t...
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ISBN:
(纸本)9781467357692;9781467357678
Network delays and packet losses are two critical parameters for the performance of networked control systems (NCS) in non-deterministic packet networks, such as the Internet. To avoid the need of a remote location, the laboratory experiences in teleoperation or telerobotics uses network simulators to reproduce the delays and packet losses. this paper presents an Internet emulation system that performs as a sensor of Internet delays and packet losses and as an actuator that reproduces these parameters into a local data flow. the paper presents some comparative results and makes a performance analysis of the whole system.
In this paper, a new approach to the data-driven PID control design in parameter space is proposed. Namely, first, volume data of the PID gains that are falsified by a necessary condition for the maximum sensitivity c...
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ISBN:
(纸本)9781467357692;9781467357678
In this paper, a new approach to the data-driven PID control design in parameter space is proposed. Namely, first, volume data of the PID gains that are falsified by a necessary condition for the maximum sensitivity constraint is calculated, and next it is visualized by volume rendering. Because of the recent development of parallel computation and GPU(graphics processing unit), rendering can be easily applied, and our main issue is how fast the volume data can be calculated by the parallel computation. We give an estimation method of the l(2) gain using a filter bank from a finite length response data, and this method is used for the volume data calculation at ten-thousand grid points. Efficiency and accuracy of our algorithm are examined by numerical experiments.
In this paper we propose a complete framework that enables big-data tools to execute sequential computervision algorithms in a scalable and parallel mechanism with limited modifications. Our main objective is to para...
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ISBN:
(纸本)9781538672662
In this paper we propose a complete framework that enables big-data tools to execute sequential computervision algorithms in a scalable and parallel mechanism with limited modifications. Our main objective is to parallelize the processing operation in order to speed up the required processing time. Most of the present big-data processing frameworks distribute the input data randomly across the available processing units to utilize them efficiently and preserve working load fairness. therefore, the current big-data frameworks are not suitable for processing huge video data content due to the existence of interframe dependency. When processing such sequential computervision algorithms on big-data tools, splitting the video frames and distributing them on the available cores will not yield the correct output and will lead to inefficient usage of underlying processing resources. Our proposed framework divides the input big-data video files into small chunks that can be processed in parallel without affecting the quality of the resulting output. An intelligent data grouping algorithm was developed to distribute these data chunks among the available processing resources and gather the results out of each chunk using Apache Storm. the proposed framework was evaluated against several computervision algorithms and achieved a speedup from 2.6x up to 8x based on the algorithm.
the data (color, texture, shape, pattern) of food products obtained from photos taken with cameras have been used in all phases from production until they get through to end-user. In this view, the main object of this...
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ISBN:
(纸本)9781665467544
the data (color, texture, shape, pattern) of food products obtained from photos taken with cameras have been used in all phases from production until they get through to end-user. In this view, the main object of this study is to analyze controlling the drying process withcomputervision used in keeping and storing food and both manage the quality control phase and determine to finalize drying phase. Another object of the study is to show that the performance and quality of drying process and other parameters under different conditions (heat source, moisture, temperature etc.) can be observable by using image analyses. In accordance withthese objects, food drying process withthree different heat sources has been analyzed, food pictures have been taken with RGB cameras during drying process and the results have been modeled. According to the modeling results, the lowest error in training data and test data have been obtained with resistance drying (1.3493 MAE and 1.8446 RMSE) and infrared (6.3375 MAE and 7.0520 RMSE), successively. It has been seen that the resistance values have almost produced the best results in terms of R2 values. these error values staying between the acceptable limits while using the simple modeling can obtain more accurate results when they are used with improved modeling techniques by increasing the data number. this situation has shown that the drying process can be controlled withcomputervision.
A computervision system was developed for the automated detection of pedestrians. the accuracy of the pedestrian detector in detecting pedestrian presence and estimating volume were evaluated. A key factor in the dev...
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ISBN:
(纸本)0852967012
A computervision system was developed for the automated detection of pedestrians. the accuracy of the pedestrian detector in detecting pedestrian presence and estimating volume were evaluated. A key factor in the development of the vision algorithms was the quality of the evaluation system used to assess their performance. An evaluation system which is representative, repeatable, and automated was achieved based on digitization and on-off manual analysis of test video sequences.
computervision systems are increasingly used for the early detection of skin diseases, such as malignant melanoma. the various proposals of computervision systems are characterized by some fundamental common phases:...
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ISBN:
(纸本)9781538681619
computervision systems are increasingly used for the early detection of skin diseases, such as malignant melanoma. the various proposals of computervision systems are characterized by some fundamental common phases: image acquisition, pre-processing, segmentation, features extraction and selection and finally classification. In most of the related papers dealing withthis topic, many features are extracted in order to feed classifiers from the simplest to the most sophisticated. Features are typically extracted using digital image processing methods (i.e., segmentation, edge detection and color and structure processing), and an open discussion about the meaning of these features and the objective ways of measuring them is ongoing. therefore, the need to investigate this topic in order to find a guideline to support new researchers on these issues arises. the present work is a not exhaustive review of the most frequently used features in the elaboration of computervision systems. the shortcomings in some of the existing studies are highlighted and suggestions for future research are provided.
computer simulation programs are designed to study the dynamic interaction of neural populations in the visual cortex. the purpose is to examine the hypothesis that cooperative intracortical interactions among these c...
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computer simulation programs are designed to study the dynamic interaction of neural populations in the visual cortex. the purpose is to examine the hypothesis that cooperative intracortical interactions among these cells, coupled withtheir assumed anisotropic connectivity, give rise to the orientation tuning observed in single neurons.
Withthe rapid development of computervision technology and the wide use of cameras, vision-based positioning has become a new research hot spot. Higher accuracy, lower cost, wider range of applications and some othe...
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ISBN:
(纸本)9781538665657
Withthe rapid development of computervision technology and the wide use of cameras, vision-based positioning has become a new research hot spot. Higher accuracy, lower cost, wider range of applications and some other advantages make vision-based positioning technology more promising than traditional positioning methods. this paper gives a briefly introduction of different methods of positioning firstly. then we discuss different technologies of vision-based positioning techniques and their core algorithms. In addition, we compared the advantages and disadvantages of different algorithms. Finally, we investigate different applications of vision-based positioning and analyze the existing problems and possible development trends.
In this paper, an efficient approach for tablets vision inspection is proposed, which can detect missing and broken individual tablets in each blister after they are sealed. the images of tablets in blister can be obt...
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ISBN:
(纸本)9781424441983
In this paper, an efficient approach for tablets vision inspection is proposed, which can detect missing and broken individual tablets in each blister after they are sealed. the images of tablets in blister can be obtained clearly using multi-lights. From these images the regions of tablets are segmented through thresholding method and the tablets' shape contours are obtained by Canny edge detector the Fourier descriptors of closed contours are carried out to extract the tablets' feature and a new classification algorithm based on support. vector machine for quality level of tablets packing are presented. the experimental results showed that 88.9% classification accuracy was achieved with a linear kernel, 95.6% with a polynomial kernel, and 99.2% with a Gaussian radial basis function kernel. the machine vision system developed has a large potential to assist in the inspection of tablets quality level classification.
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