Ultra low delay video transmission is becoming increasingly important. Video-based applications with ultra low delay requirements range from teleoperation scenarios such as controlling drones or telesurgery to autonom...
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ISBN:
(纸本)9781467399616
Ultra low delay video transmission is becoming increasingly important. Video-based applications with ultra low delay requirements range from teleoperation scenarios such as controlling drones or telesurgery to autonomous control of dynamic processes using computer vision algorithms applied on real-time video. To evaluate the performance of the video transmission chain in such systems, it is important to be able to precisely measure the glass-to-glass (G2G) delay of the transmitted video. In this paper, we present a low-complexity system that takes a series of pairwise independent measurements of G2G delay and derives performance metrics such as mean delay or minimum delay etc. from the data. The precision is in the sub-millisecond range, mainly limited by the sampling rate of the measurement system. In our implementation, we achieve a G2G measurement precision of 0.5 milliseconds with a sampling rate of 2kHz.
image technologies nowadays are used not only for keeping personal events safe, but also are widely applied in conjunction with automated electronic systems. Computer vision is widely used for inspection of the produc...
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ISBN:
(纸本)9781509018666
image technologies nowadays are used not only for keeping personal events safe, but also are widely applied in conjunction with automated electronic systems. Computer vision is widely used for inspection of the production quality in industries. Food industry is not an exception. Containers for food industry are made in very large quantities. This article contains of defect analysis of both external and side area of the bottleneck. Defects were divided into groups according to which the filters are created. For the control of PET preparation quality an automated computer vision algorithms were developed. The algorithms and methods were used for the detection of defective products mainly based on the image segmentation, digital production, erosion, smoothing. The most effective filters for the defect detection of the workpieces have been determined. It was carried out that efficiency of algorithms are close to 100 %.
image pattern recognition is an important area in digital imageprocessing. An efficient pattern recognition algorithm should be able to provide correct recognition at a reduced computational time. Off late amongst th...
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ISBN:
(纸本)9781509010660
image pattern recognition is an important area in digital imageprocessing. An efficient pattern recognition algorithm should be able to provide correct recognition at a reduced computational time. Off late amongst the machine learning pattern recognition algorithms, Artificial fish swarm algorithm is one of the swarm intelligence optimization algorithms that works based on population and stochastic search. In order to achieve acceptable result, there are many parameters needs to be adjusted in AFSA. Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters. In standard AFSA, these two parameters remain constant until the algorithm termination. Large values of these parameters increase the capability of algorithm in global search, while small values improve the local search ability of the algorithm. In this paper, we empirically study the performance of the AFSA and different approaches to balance between local and global exploration have been tested based on the adaptive modification of visual and step during algorithm execution. The proposed approaches have been evaluated based on the four well-known benchmark functions. Experimental results show considerable positive impact on the performance of AFSA. A Convex optimization has been integrated into the proposed work to have an ideal segmentation of the input image which is a MR brain image.
The artificial vision is a part of the artificial intelligence that pretends to simulate the human vision, is to say, from the acquisition, processing, analysis and interpretation of images through an intelligent syst...
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ISBN:
(纸本)9781509050475
The artificial vision is a part of the artificial intelligence that pretends to simulate the human vision, is to say, from the acquisition, processing, analysis and interpretation of images through an intelligent system. This work presents the creation of prototypes under the game jam model as a software product. In this context, the objective of the present work was to apply basic artificial vision algorithms such as linear discriminant analysis (LDA), principal component analysis (PCA), Fisherface, Otsu, CamShift and color spaces such as RGB and HSV in order to be able to motion detection of objects, face recognition and pedestrian detection. As a result of applying this model in rapid prototyping, we found significant factors (such as: participatory design, light construction, product value approach, aesthetics and technology) in the implementation of innovative strategies in creating of prototypes focused on Software development.
Lossy image compression algorithms are pervasively used to reduce the size of images transmitted over the web and recorded on data storage media. However, we pay for their high compression rate with visual artifacts d...
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ISBN:
(纸本)9781509061839
Lossy image compression algorithms are pervasively used to reduce the size of images transmitted over the web and recorded on data storage media. However, we pay for their high compression rate with visual artifacts degrading the user experience. Deep convolutional neural networks have become a widespread tool to address high-level computer vision tasks very successfully. Recently, they have found their way into the areas of low-level computer vision and imageprocessing to solve regression problems mostly with relatively shallow networks. We present a novel 12-layer deep convolutional network for image compression artifact suppression with hierarchical skip connections and a multi-scale loss function. We achieve a boost of up to 1.79 dB in PSNR over ordinary JPEG and an improvement of up to 0.36 dB over the best previous ConvNet result. We show that a network trained for a specific quality factor (QF) is resilient to the QF used to compress the input image - a single network trained for QF 60 provides a PSNR gain of more than 1.5 dB over the wide QF range from 40 to 76.
Identifying similarities in large datasets is an essential operation in several applications such as bioinformatics, pattern recognition, and data integration. To make a relational database management system similarit...
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Identifying similarities in large datasets is an essential operation in several applications such as bioinformatics, pattern recognition, and data integration. To make a relational database management system similarity-aware, the core relational operators have to be extended. While similarity-awareness has been introduced in database engines for relational operators such as joins and group-by, little has been achieved for relational set operators, namely Intersection, Difference, and Union. In this paper, we propose to extend the semantics of relational set operators to take into account the similarity of values. We develop efficient query processingalgorithms for evaluating them, and implement these operators inside an open-source database system, namely PostgreSQL By extending several queries from the TPC-H benchmark to include predicates that involve similarity-based set operators, we perform extensive experiments that demonstrate up to three orders of magnitude speedup in performance over equivalent queries that only employ regular operators. (C) 2015 Elsevier Ltd. All rights reserved.
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super resolution algor...
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ISBN:
(纸本)9781467399616
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super resolution algorithms to realize an increased resolution. Those methods can be divided into approaches that rely on only a single low resolution image or on multiple low resolution video frames. While incorporating more frames into the super-resolution is beneficial for the resolution enhancement in principle, it is also likely to introduce more artifacts from inaccurate motion estimation. To alleviate this problem, various weightings have been proposed in the literature. In this paper, we propose an extended dual weighting scheme for an interpolation-based super-resolution method based on Voronoi tessellation that relies on both a motion confidence weight and a distance weight. Compared to non-weighted super-resolution, the proposed method yields an average gain in luminance PSNR of up to 1.29 dB and 0.61 dB for upscaling factors of 2 and 4, respectively. Visual comparisons substantiate the objective results.
OCR is the most active, interesting evaluation invention of text cum character processing recognition and pattern based image recognition. In present life OCR has been successfully using in finance, legal, banking, he...
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ISBN:
(纸本)9781467385879
OCR is the most active, interesting evaluation invention of text cum character processing recognition and pattern based image recognition. In present life OCR has been successfully using in finance, legal, banking, health care and home need appliances. The OCR consists the different levels of processing methods like as image Pre Acquisition, Classification, Post-Acquisition, Pre-Level processing, Segmented processing, Post-Level processing, Feature Extraction. The many researchers are proposed various levels of different methodologies and approaches in different versions of languages with help of modern and traditional technologies. This paper expressed the detail study and analysis of various character recognition methods and approaches: in details like as flow and type of approached methodology was used, type of algorithm has built with support of technology has implemented background of the proposed methodology and invention best outcomes flow for the each methodology. This paper and also expressed the main objectives and ideology of various OCR algorithms, like as neural networks algorithm, structural algorithm, support vector algorithm, statistical algorithm, template matching algorithm along with how they classified, identified, rule formed, inferred for recognition of characters and symbols.
In this paper we present a new, publicly available database of color, high resolution images useful in evaluation of various algorithms in the field of video surveillance. The additional data provided with the images ...
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ISBN:
(纸本)9783319238142;9783319238135
In this paper we present a new, publicly available database of color, high resolution images useful in evaluation of various algorithms in the field of video surveillance. The additional data provided with the images facilitates the evaluation of tracking, recognition and reidentification across sequences of images.
We address the problem of position control of micro-chips (chiplets) immersed in dielectric fluid. An electric field, shaped by controlling the voltages of spiral shaped electrodes, is used to reliably and accurately ...
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ISBN:
(纸本)9781509045839
We address the problem of position control of micro-chips (chiplets) immersed in dielectric fluid. An electric field, shaped by controlling the voltages of spiral shaped electrodes, is used to reliably and accurately transport and position chiplets using dielectrophoretic forces. A lumped, capacitive based (nonlinear) motion model is used to generate an open loop control policy. The open loop policy is generated using a one step model predictive control approach. By exploiting the spatial symmetry and periodicity of the open loop control solution, a real-time control scheme is designed by applying simple algebraic operations to a base function defined on a finite domain. The chiplet position is tracked using imageprocessingalgorithms. We demonstrate the validity of our approach by describing an experimental result, where real-time control is used to move a chiplet for 1000μm in a controlled manner.
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