In order to improve the segmentation accuracy of adhered rice images, an automatic segmentationalgorithm for adhered rice images based on background skeleton features is proposed. The experimental results show that t...
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ISBN:
(数字)9781728161068
ISBN:
(纸本)9781728161075
In order to improve the segmentation accuracy of adhered rice images, an automatic segmentationalgorithm for adhered rice images based on background skeleton features is proposed. The experimental results show that the proposed algorithm can adapt well to the adhesion segmentation of different grains under complex condition. Compared with the classic distance transformation watershed algorithm and the improved watershed algorithm, algorithm accuracy has improved a lot, and the formed grain segmentation boundary is smoother, with less influence on the shape.
Variable rate pesticide application holds Great potential in precision agriculture where application efficiency depends mainly on plant recognition. The segmentation of the plant from the background is key to plant re...
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Variable rate pesticide application holds Great potential in precision agriculture where application efficiency depends mainly on plant recognition. The segmentation of the plant from the background is key to plant recognition. The work presented in this paper is a real-time segmentationalgorithm that was developed to improve the quality of plant segmentation under natural outdoor light conditions. The plant images were greyed with the colour features H, a*, I3 and Cr respectively, and the plant was segmented from the grey images with a threshold that was computed by an iterative method. Experiments showed that segmentation was generally of good quality if the background was bare soil. The quality of segmentation declines if the images are greyed by H and Cr, and the quality remains stable if they are greyed by a* and I3 when the background is complicated, and, especially with heavy shadows. With respect to segmentation speed, that greyed by Cr was the fastest and that greyed by a* was slowest amongst the four.
Variable rate pesticide application holds great potential in precision agriculture where application efficiency depends mainly on plant recognition .The segmentation of the plant from the background is key to plant **...
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Variable rate pesticide application holds great potential in precision agriculture where application efficiency depends mainly on plant recognition .The segmentation of the plant from the background is key to plant *** work presented in this paper is a real-time segmentationalgorithm that was developed to improve the quality of plant segmentation under natural outdoor light *** plant images were greyed with the colour features H,a,I3 and Cr respectively, and the plant was segmented from the grey images with a threshold that was computed by an iterative *** showed that segmentation was generally of good quality if the background was bare *** quality of segmentation declines if the images are greyed by H and Cr,and the quality remains stable if they are greyed by a and I3 when the background is complicated,and,especially with heavy *** respect to segmentation speed, that greyed by Cr was the fastest and that greyed by a was slowest amongst the four.
Clustering analysis is an unsupervised classification method,which classifies the samples by classifying the *** the absence of prior knowledge,the imagesegmentation can be done by cluster *** paper gives the concept...
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Clustering analysis is an unsupervised classification method,which classifies the samples by classifying the *** the absence of prior knowledge,the imagesegmentation can be done by cluster *** paper gives the concept of clustering analysis and two common cluster algorithms,which are FCM and K-Means *** applications of the two clustering algorithms in imagesegmentation are explored in the paper to provide some references for the relevant researchers.
An automatic segmentationalgorithm which combine visual attention mechanism and GrabCut is presented, in order to meet the automation needs of imagesegmentation. Firstly, using visual attention mechanism to get the ...
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ISBN:
(纸本)9781510822030
An automatic segmentationalgorithm which combine visual attention mechanism and GrabCut is presented, in order to meet the automation needs of imagesegmentation. Firstly, using visual attention mechanism to get the initial target areas, and then compensate the edge of the areas, finally using GrabCut to get accurate segmentation results. The experimental results show that this method can finish the imagesegmentation automatically and has good accuracy.
Pattern regeneration is one of the applications of reverse engineering technology in the textile field, which realises the process of textile-pattern regeneration-textile, and fundamentally provides an intelligent des...
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Pattern regeneration is one of the applications of reverse engineering technology in the textile field, which realises the process of textile-pattern regeneration-textile, and fundamentally provides an intelligent design means of textile. At present, the method of pattern regeneration in the jacquard fabric is to use the image segmentation algorithm to segment the image digitalised by unidirectional imaging, and then the segmented pattern could be identified to regeneration for the design of new fabrics. However, due to the concave and convex pattern textures on the surface of jacquard fabric, the traditional unidirectional imaging method cannot be used for the full characterisation of its structural information, resulting in unsatisfactory pattern segmentation effect. To solve this problem, a novel segmentationalgorithm for jacquard patterns based on multi-view image fusion was proposed in this study. Based on multi-view image acquisition and fusion, the pattern image of jacquard fabric could be cluster-segmented by extracting the complete texture information of the fused image and the actual colour information of the calibrated image. Compared with the traditional unidirectional imaging method, the experimental results show that the enhanced texture information of the fused image is more workable for the pattern segmentation, it validates the effectiveness of the proposed method.
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo ***,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy...
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The visual noise of each light intensity area is different when the image is drawn by Monte Carlo ***,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed *** we propose a rendered image denoising method with filtering guided by lighting ***,we design an image segmentation algorithm based on lighting information to segment the image into different illumination ***,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination *** different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area ***,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the *** the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on *** shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
Creep-feed belts grinding (CFBG) can improve processing efficiency while ensuring the surface quality of TC4 titanium alloy materials. However, the difficult-to-machine characteristics of titanium alloys and the singl...
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Creep-feed belts grinding (CFBG) can improve processing efficiency while ensuring the surface quality of TC4 titanium alloy materials. However, the difficult-to-machine characteristics of titanium alloys and the single-layer abrasive nature of the abrasive belts accelerate belt wear. Meanwhile, grinding creates micron-level scratches on the surface, which can lead to localized stress concentration on the titanium alloy surface and significantly reduce the service performance of workpiece. Due to the randomness of the grain and the complexity of grinding process, which makes it a challenging problem to investigate the regularity and mechanism of the surface morphology characteristics with belt wear under different grinding forms. Therefore, this research proposes a surface topography evaluation method of titanium alloy based on YOLOv8 segmentationalgorithm, and explores the regularity of surface topography after creep-feed/conventional abrasive belt (CBG) wear. Firstly, the YOLOv8 algorithm was used to segment the collected titanium alloy surface topography images. Accuracy of the algorithm is 0.85, Precision, Recall and F1 values are 0.85, 0.72, F1 and 0.78 respectively, which indicates that the algorithm performs relatively well. Secondly, the surface morphology characterization regularity was quantitatively characterized;with belt wear, the area ratio, perimeter ratio and depth of scratches in CBG gradually decreased, and the aspect ratio, fractal dimension and radius of curvature gradually increased;while in CFBG, the parameters all changed rapidly (decreasing/increasing) and the value then fluctuated within a range. Finally, a model of titanium alloy surface morphology molding in the whole life cycle of abrasive belts under different grinding methods was established.
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and *** detection methods have limitations in terms of real-time performance and monitoring...
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Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and *** detection methods have limitations in terms of real-time performance and monitoring *** address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
In order to improve the accuracy of user's position solution using Global Navigation Satellite System (GNSS) in urban canyons, it is important to know whether a satellite's signal is obstructed by surrounding ...
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ISBN:
(纸本)9781467384025
In order to improve the accuracy of user's position solution using Global Navigation Satellite System (GNSS) in urban canyons, it is important to know whether a satellite's signal is obstructed by surrounding buildings. This can be accomplished by using an upward-facing camera and segmenting the image into sky and non-sky. This paper evaluates the Otsu, Mean Shift, Graph cut and HMRF-EM-imageimage segmentation algorithms for this purpose. Since some algorithms provide two or more categories, segmentation is followed by k-means clustering techniques to yield only two categories;sky and non-sky. The algorithms are tested using images taken using an upwardfacing camera at roughly the same locations in different weather conditions: cloudy and sunny. Result shows that, when images are appropriately adjusted, the Otsu method overcomes the three other algorithms in terms of the percentage of sky accurately segmented and is also more computationally efficient. Experiment was also perform in Calgary downtown to show the effect of segmentation on the GNSS accuracy. Results show that, when obstructed satellites are removed, the RMS of the residuals decreases significantly compare to when all satellites are used.
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