In the current era of large scale distributed computing, users voluntarily donate computation power of their idle computers or desktop machines. However, there is an urgent need of a utility-based distributed problem ...
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In the current era of large scale distributed computing, users voluntarily donate computation power of their idle computers or desktop machines. However, there is an urgent need of a utility-based distributed problem solving environment to attract more users. Related to applying the utility concept, we are working on design and implementation of a distributed image processing system that uses: 1) contract net protocol for task assignment;2) concept of utility-based distributed computing;3) task graph concept for application design. In this paper, we present our results of the design aspects of the system. We propose the design of contract net protocol-based distributed image processing system and analyse characteristics of the proposed system. We evaluate and select available options for implementation of the system. The proposed system allows transparent execution of task graph-based applications in a distributed environment.
The challenge of bringing more intelligence to the infrastructure of modern cities requires a change of thinking and states a demand for new algorithms and strategies. One important outcome of those algorithms is a re...
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ISBN:
(纸本)9781479937554
The challenge of bringing more intelligence to the infrastructure of modern cities requires a change of thinking and states a demand for new algorithms and strategies. One important outcome of those algorithms is a realtime estimation of the prevalent spatio-temporal conditions of public transportation networks by making use of distributed image processing on networked smart camera systems. This paper provides a detailed analysis of two exemplary networked applications that can use the derived data. A conducted simulation study based on the infrastructure of real cities shows the potential of using autonomously generated knowledge, that smart camera systems can provide. Especially, inter-camera object tracking, as well as adaptive and smart navigation tasks can benefit considerably and substantiate the need for autonomous and confidential imageprocessing.
a decretive concern in distributed computing systems is to efficiently schedule the tasks among all processors so that the overall processing time of the submitted tasks is at a minimum. In this article, following the...
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ISBN:
(纸本)9781467347716;9781467347723
a decretive concern in distributed computing systems is to efficiently schedule the tasks among all processors so that the overall processing time of the submitted tasks is at a minimum. In this article, following the recently evolved paradigm, referred to as is divisible load theory (DLT), we conducted an experimental study on the time performance to processes a large volume of image data on a network of workstations. We present our program model and timing mechanism for the distributed image processing and finally display effects of delta parameter and test cases in our mentioned algorithm.
A decretive concern in distributed computing systems is to efficiently schedule the tasks among all processors so that the overall processing time of the submitted tasks is at a minimum. In this article, following the...
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ISBN:
(纸本)9781467347709
A decretive concern in distributed computing systems is to efficiently schedule the tasks among all processors so that the overall processing time of the submitted tasks is at a minimum. In this article, following the recently evolved paradigm, referred to as divisible load theory (DLT), we conducted an experimental study on the time performance to process a large volume of image data on a network of workstations. We present our program model and timing mechanism for the distributed image processing and finally display effects of δ parameter and test cases in our mentioned algorithm.
With the increase in the number of images from various channels such as a vehicle's black box, CCTV and drone, the amount of data related to the vehicles and the traffic situations is also explosively increasing. ...
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ISBN:
(纸本)9781538647547
With the increase in the number of images from various channels such as a vehicle's black box, CCTV and drone, the amount of data related to the vehicles and the traffic situations is also explosively increasing. Also, the greatly increased image data analysis is further emphasizing the importance of large-scale image data processing. In this regard, this study proposed and designed a distribution system using Kafka. For high-speed processing of data, black box image frames were distributed to several nodes using Kafka, a real-time message distribution processing system. Moreover, by setting the frame of black box image as input to each node, the localization of car license plates through imageprocessing, and segmented character recognition were explored.
The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model...
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The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model in its sequential form is computationally intensive and operates on large data sets. This paper presents another framework to implement the standard version of the AAM model. We suggest a distributed and parallel approach justified by the characteristics of the model and their potentialities. We introduce a schema for the representation of the overall model and we study of operations that can be parallelized. This approach is intended to exploit the benefits build in the area of advanced imageprocessing.
The Canny edge detector is one of the most widely used edge detection algorithms due to its superior performance. Unfortunately, not only is it computationally more intensive as compared with other edge detection algo...
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The Canny edge detector is one of the most widely used edge detection algorithms due to its superior performance. Unfortunately, not only is it computationally more intensive as compared with other edge detection algorithms, but it also has a higher latency because it is based on frame-level statistics. In this paper, we propose a mechanism to implement the Canny algorithm at the block level without any loss in edge detection performance compared with the original frame-level Canny algorithm. Directly applying the original Canny algorithm at the block-level leads to excessive edges in smooth regions and to loss of significant edges in high-detailed regions since the original Canny computes the high and low thresholds based on the frame-level statistics. To solve this problem, we present a distributed Canny edge detection algorithm that adaptively computes the edge detection thresholds based on the block type and the local distribution of the gradients in the image block. In addition, the new algorithm uses a nonuniform gradient magnitude histogram to compute block-based hysteresis thresholds. The resulting block-based algorithm has a significantly reduced latency and can be easily integrated with other block-based image codecs. It is capable of supporting fast edge detection of images and videos with high resolutions, including full-HD since the latency is now a function of the block size instead of the frame size. In addition, quantitative conformance evaluations and subjective tests show that the edge detection performance of the proposed algorithm is better than the original frame-based algorithm, especially when noise is present in the images. Finally, this algorithm is implemented using a 32 computing engine architecture and is synthesized on the Xilinx Virtex-5 FPGA. The synthesized architecture takes only 0.721 ms (including the SRAM READ/WRITE time and the computation time) to detect edges of 512 x 512 images in the USC SIPI database when clocked at 100 MHz
This paper describes a low-cost distributed computing approach for the post-processing of videos. It has been implemented to support the creation of composite videos from various video sources, and supports image mani...
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ISBN:
(纸本)9781424440894
This paper describes a low-cost distributed computing approach for the post-processing of videos. It has been implemented to support the creation of composite videos from various video sources, and supports image manipulation on individual frames of the video. The principle deployment scenario for this work has been to support the automatic creation of output video based on traditional face-to-face lectures. Experimental results suggest that this approach can lead to significant speedups with a reduction in operating costs by leveraging existing underutilized equipment.
Hybrid clouds are combinations of private, community and/or public clouds, and allow the creation of "cloud bursting" deployment models, in which part of the data processing is done in a private cloud and re...
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ISBN:
(纸本)9780769550459
Hybrid clouds are combinations of private, community and/or public clouds, and allow the creation of "cloud bursting" deployment models, in which part of the data processing is done in a private cloud and resources from public clouds are used when needed. This model is particularly interesting for CPU-intensive scientific data processing. In order to help determine in which conditions part of the whole of a large data processing task must be sent to a public or private cloud, dynamic benchmarks are required. In this paper we propose an imageprocessing-based test bench that monitors the performance of the clouds resources to gather useful statistics and to determine which resource should be used for a specific task, in order to reduce costs and running time.
This study aims at building an autonomous robot that is capable of comprehending complicated imageprocessing algorithms rapidly and concurrently via a wireless communication network. The entire system includes a mobi...
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ISBN:
(纸本)9781934272169
This study aims at building an autonomous robot that is capable of comprehending complicated imageprocessing algorithms rapidly and concurrently via a wireless communication network. The entire system includes a mobile robot, a network camera mounted on the mobile robot, a wireless LAN, and a distributed image processing system. images captured by the network camera are first transmitted to one of the clustered computers through the wireless LAN. The computer receiving the images then distributes the images to the other computers in the cluster. The imageprocessing results will be collected and reported back to the robot through the wireless LAN also by the same computer. With the clustered computers, multiple image-processing algorithms could be applied to a single image in a concurrent fashion. As an experiment, the mobile robot has been put on a street. In order for the mobile robot to move autonomously on the street, three targets including white lines on the road, static and moving obstacles, have been identified necessary for the distributed image processing system to detect. The experimental results indicate that the distributed image processing system successfully meet the needs for the autonomous movement of the mobile robot.
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