In recent years,UAV(Unmanned Aerial Vehicle)becomes more and more popular and it is put into operation in various fields,such as agricultural irrigation,geological exploration and so *** this paper,an unmanned aerial ...
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In recent years,UAV(Unmanned Aerial Vehicle)becomes more and more popular and it is put into operation in various fields,such as agricultural irrigation,geological exploration and so *** this paper,an unmanned aerial vehicle target detection and ranging system based on OpenCV and Tensor Flow is discussed,which can detect and avoid obstacles in time,improving the service life and intelligence level of the unmanned aerial ***,gray-scale need to be put on the image captured by the *** Gaussian denoising,Sobel operator is applied for edge ***,target recognition is carried out by using OpenCV and Tensor Flow,following by which is distance measurement,on the basis of OpenCV and video ***,the measurement results can be obtained.
Due to the growing number of applications for additive manufacturing (AM) there is an increasing need for enhanced quality control methods. One approach is the in-situ analysis of manufactured workpiece contours layer...
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Due to the growing number of applications for additive manufacturing (AM) there is an increasing need for enhanced quality control methods. One approach is the in-situ analysis of manufactured workpiece contours layer by layer and the associated melting pool dimensions to ensure the conformity with the geometrical product specifications. For this purpose an accurate optical detection of the workpiece contour in combination with an alignment to the ideal layer model is needed. Considering a selective laser sintering (SLS) process, edge-detectionalgorithms have been compared and applied with improved settings. Image sets with varying illumination conditions of different directions are recorded and evaluated. In addition, the influences of the resulting shadows at the contour edges have been investigated. In this context filter methods are tested to further optimize the captured images for the detection process. Consequently an adapted in-situ measurement system is implemented to achieve the specific requirements of powder bed based additive manufacturing processes.
Spiral concentrators are robust gravity separation devices that allow for concentration of slurry streams. Optimal splitter position (which determines recovery and grade) is dependent on the interface positions of the...
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Due to the great interest of the automotive industry to quickly and systematically evaluate low wear quantities a new approach based on image processing is presented. By comparing the captured rough surface point clou...
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edgedetection is one of the most important concepts in image processing which is used as an indicator for processing and extraction of some of border characteristics at low levels, also for detection and finding obje...
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ISBN:
(纸本)9781467378130
edgedetection is one of the most important concepts in image processing which is used as an indicator for processing and extraction of some of border characteristics at low levels, also for detection and finding objects at high levels. Due to the inherently parallel nature of edge detection algorithms, they suit well for implementation on a Graphics Processing Unit (GPU). First part of this paper aims to detect and retouch image edges using fuzzy inference system. In the first step RGB images converted to grayscale images. In the second step the input images are converted from uint8 class to double class. In the third step, fuzzy inference system isdefined with two inputs. Fuzzyinference system rules and membership function are applied on these two inputs. The outputwith black pixels indicatesareas with edge and the output with white pixels indicates areas without edge. Thesecond part of this paper, the performance of fuzzy edgedetection algorithm is improved using GPU platformby exploiting data-level parallelism and scatter/gather parallel communication patterninMatlab environment. The experimental results show that the performance is improved for different image sizes of up to 11.8 x.
Wave observation represented water surface elevation at a reference point is basic and essential data for ocean and coastal engineering that is mostly measured with traditional wave gauges, for instance capacitance, r...
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Wave observation represented water surface elevation at a reference point is basic and essential data for ocean and coastal engineering that is mostly measured with traditional wave gauges, for instance capacitance, resistance and conductivity types. Therefore, accuracy and exactness are the most important aspects of data acquisition systems. In this study, we focus on the development of image processing techniques for wave measurement in a wave flume as a tool to replace traditional wave gauges, which are complicated to use, costly and intrusive. Recently, image processing techniques have been developed for utilization in various tasks. The main factors that influence the accuracy of these techniques are image quality, algorithm performance and exact calibration. Image processing techniques based on edge detection algorithms were used to measure waves in the laboratory with a camera. The experimental results showed the agreement of water surface elevation from both measurement methods. The average wave height and average wave period of regular wave obtained from the zero up-crossing analysis were different by less than 10% and 1% respectively compared with traditional wave gauges. Moreover, this algorithm can also measure irregular waves in hydraulic laboratories as well. Hence, this approach is a new, alternative tool for use in wave flume measurement, with good results.
A novel FPGA- based architecture for Sobel edgedetection algorithm has been proposed. The Sobel algorithm is chosen due to its property of providing a differencing as well as noise smoothing operation in the single k...
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A novel FPGA- based architecture for Sobel edgedetection algorithm has been proposed. The Sobel algorithm is chosen due to its property of providing a differencing as well as noise smoothing operation in the single kernel. Thus, noise sensitivity of first gradient based operations can be avoided by the use of this algorithm. The implementation of edge detection algorithms on a field programmable gate array ( FPGA) is motivated by the fact that large memory FPGAs are now available, providing a platform for processing real time algorithms on application- specific hardware with substantially higher performance than programmable digital signal processors ( DSPs). This architecture can be used as a building block of a pattern recognition system, autonomous robot navigation, and also as a system for creating an image dazzling effect in multimedia graphics. This architecture is implicitly pipelined to provide a system capable of operating at a clock speed of 99.499MHz which is a significant improvement over programmable DSPs implementation.
An approach for subpixel edge positioning and part sizing by coherent shadow projection is described. Templates matching the Fresnel diffraction pattern at the shadow borders are used to locate precisely the edges by ...
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An approach for subpixel edge positioning and part sizing by coherent shadow projection is described. Templates matching the Fresnel diffraction pattern at the shadow borders are used to locate precisely the edges by an iterative cross-correlation procedure. A similar procedure is followed to compensate for longitudinal displacements by monitoring their effects on the diffraction pattern. The performance is analysed in the presence of mechanical, optical and electronic perturbations. A resolution of nearly 0.015 pixels and an accuracy of 0.15 pixels have been obtained.
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