The commercial high-resolution imaging satellite with 1 m spatial resolution IKONOS is an important data source of information for urban planning and geographical information system (GIS) applications. In this paper, ...The commercial high-resolution imaging satellite with 1 m spatial resolution IKONOS is an important data source of information for urban planning and geographical information system (GIS) applications. In this paper, a morphological method is proposed. The proposed method combines the automatic thresholding and morphological operation techniques to extract the road centerline of the urban environment. This method intends to solve urban road centerline problems, vehicle, vegetation, building etc. Based on this morphological method, an object extractor is designed to extract road networks from highly remote sensing images. Some filters are applied in this experiment such as line reconstruction and region filling techniques to connect the disconnected road segments and remove the small redundant. Finally, the thinning algorithm is used to extract the road centerline. Experiments have been conducted on a high-resolution IKONOS and QuickBird images showing the efficiency of the proposed method.展开更多
The visual inspection is an economical and effective method for welding. For measuring the feature sizes of grooves,a method based on line structured light is presented. Firstly,an adaptive algorithm to extract the su...The visual inspection is an economical and effective method for welding. For measuring the feature sizes of grooves,a method based on line structured light is presented. Firstly,an adaptive algorithm to extract the subpixel centerline of structured light stripes is introduced to deal with the uneven width and grayscale distributions of laser stripes,which is based on the quadratic weighted grayscale centroid. By means of region-of-interest(ROI)division and image difference,an image preprocessing algorithm is developed for filtering noise and improving image quality. Furthermore,to acquire geometrical dimensions of various grooves and groove types precisely,the subpixel feature point extraction algorithm of grooves is designed. Finally, experimental results of feature size measuring show that the absolute error of measurement is 0.031—0.176 mm,and the relative error of measurement is 0.2%—3.6%.展开更多
Carotid artery stenosis causes narrowing of carotid lumens and may lead to brain infarction. The purpose of this study was to develop a semi-automated method of segmenting vessel walls, surrounding tissues, and more i...Carotid artery stenosis causes narrowing of carotid lumens and may lead to brain infarction. The purpose of this study was to develop a semi-automated method of segmenting vessel walls, surrounding tissues, and more importantly, the carotid artery lumen by contrast computed tomography angiography（CTA） images and to define the severity of stenosis and present a three-dimensional model of the carotid for visual inspection. In vivo contrast CTA images of 14 patients（7 normal subjects and 7 patients undergoing endarterectomy） were analyzed using a multi-step segmentation algorithm. This method uses graph cut followed by watershed and Hessian based shortest path method in order to extract lumen boundary correctly without being corrupted in the presence of surrounding tissues.Quantitative measurements of the proposed method were compared with those of manual delineation by independent board-certified radiologists. The results were quantitatively evaluated using spatial overlap surface distance indices. A slightly strong match was shown in terms of dice similarity coefficient（DSC） = 0.87±0.08; mean surface distance（Dmsd）= 0.32±0.32; root mean squared surface distance（Drmssd） = 0.49±0.54 and maximum surface distance（Dmax）=2.14±2.08 between manual and automated segmentation of common, internal and external carotid arteries, carotid bifurcation and stenotic artery, respectively. Quantitative measurements showed that the proposed method has high potential to segment the carotid lumen and is robust to the changes of the lumen diameter and the shape of the stenosis area at the bifurcation site. The proposed method for CTA images provides a fast and reliable tool to quantify the severity of carotid artery stenosis.展开更多
Common strong noise interferences like metal splashes,smoke,and arc light during welding can seriously pollute the laser stripe images,causing the tracking model to drift and leading to tracking failure.At present,the...Common strong noise interferences like metal splashes,smoke,and arc light during welding can seriously pollute the laser stripe images,causing the tracking model to drift and leading to tracking failure.At present,there are already many mature methods for identifying and extracting feature points of linear laser stripes.When the laser stripe forms a curved shape on the surface of the workpiece,these linear methods will no longer be applicable.To eliminate interference sources,enhance the robustness of the weld tracking model,and effectively extract the feature points of curved laser stripes under strong noise conditions.This paper proposes a Conditional Generative Adversarial Network(CGAN)based anti-interference recognition method for welding images.The generator adopts an improved U-Net++structure,adds a Multi-scale Channel Attention module(MS-CAM),introduces Deep Supervision,and proposes a Multi-output Fusion strategy(MOFS)in the output result to en-hance the image inpainting effect;the discriminator uses PatchGAN.The center of the laser stripe is obtained using the grayscale center of mass method and then combined with polynomial fitting to extract the feature points of the weld seam.The experimental results show that the PSNR of the inpainting image is 26.24 dB,the SSIM is 0.98,and the LPIPS is 0.032.The centerline of the inpainting image and the centerline of the noise-free image laser stripe are fitted with a curve.The error of centerline feature points is no more than 5%,confirming the superiority and feasibility of the method.展开更多
文摘The commercial high-resolution imaging satellite with 1 m spatial resolution IKONOS is an important data source of information for urban planning and geographical information system (GIS) applications. In this paper, a morphological method is proposed. The proposed method combines the automatic thresholding and morphological operation techniques to extract the road centerline of the urban environment. This method intends to solve urban road centerline problems, vehicle, vegetation, building etc. Based on this morphological method, an object extractor is designed to extract road networks from highly remote sensing images. Some filters are applied in this experiment such as line reconstruction and region filling techniques to connect the disconnected road segments and remove the small redundant. Finally, the thinning algorithm is used to extract the road centerline. Experiments have been conducted on a high-resolution IKONOS and QuickBird images showing the efficiency of the proposed method.
基金supported by the National Natural Science Foundation of China(No. 51975293)the Aeronautical Science Foundation of China (No. 2019ZD052010)。
文摘The visual inspection is an economical and effective method for welding. For measuring the feature sizes of grooves,a method based on line structured light is presented. Firstly,an adaptive algorithm to extract the subpixel centerline of structured light stripes is introduced to deal with the uneven width and grayscale distributions of laser stripes,which is based on the quadratic weighted grayscale centroid. By means of region-of-interest(ROI)division and image difference,an image preprocessing algorithm is developed for filtering noise and improving image quality. Furthermore,to acquire geometrical dimensions of various grooves and groove types precisely,the subpixel feature point extraction algorithm of grooves is designed. Finally, experimental results of feature size measuring show that the absolute error of measurement is 0.031—0.176 mm,and the relative error of measurement is 0.2%—3.6%.
文摘Carotid artery stenosis causes narrowing of carotid lumens and may lead to brain infarction. The purpose of this study was to develop a semi-automated method of segmenting vessel walls, surrounding tissues, and more importantly, the carotid artery lumen by contrast computed tomography angiography（CTA） images and to define the severity of stenosis and present a three-dimensional model of the carotid for visual inspection. In vivo contrast CTA images of 14 patients（7 normal subjects and 7 patients undergoing endarterectomy） were analyzed using a multi-step segmentation algorithm. This method uses graph cut followed by watershed and Hessian based shortest path method in order to extract lumen boundary correctly without being corrupted in the presence of surrounding tissues.Quantitative measurements of the proposed method were compared with those of manual delineation by independent board-certified radiologists. The results were quantitatively evaluated using spatial overlap surface distance indices. A slightly strong match was shown in terms of dice similarity coefficient（DSC） = 0.87±0.08; mean surface distance（Dmsd）= 0.32±0.32; root mean squared surface distance（Drmssd） = 0.49±0.54 and maximum surface distance（Dmax）=2.14±2.08 between manual and automated segmentation of common, internal and external carotid arteries, carotid bifurcation and stenotic artery, respectively. Quantitative measurements showed that the proposed method has high potential to segment the carotid lumen and is robust to the changes of the lumen diameter and the shape of the stenosis area at the bifurcation site. The proposed method for CTA images provides a fast and reliable tool to quantify the severity of carotid artery stenosis.
基金Supported by the"The 14th Five Year Plan"Hubei Provincial ad-vantaged characteristic disciplines(groups)project of Wuhan University of Science and Technology(Grant No.2023B0404)National Natural Science Foundation of China(Grant Nos.52275503 and 72471181)+2 种基金Hubei Provincial Outstanding Youth Fund of China(Grant No.2023AFA092)Hubei Provincial Natural Science Foundation of China(Grant No.2023AFB915)Hubei Provincial Key Research and Development Plan Project of China(Grant No.2023BAB048).
文摘Common strong noise interferences like metal splashes,smoke,and arc light during welding can seriously pollute the laser stripe images,causing the tracking model to drift and leading to tracking failure.At present,there are already many mature methods for identifying and extracting feature points of linear laser stripes.When the laser stripe forms a curved shape on the surface of the workpiece,these linear methods will no longer be applicable.To eliminate interference sources,enhance the robustness of the weld tracking model,and effectively extract the feature points of curved laser stripes under strong noise conditions.This paper proposes a Conditional Generative Adversarial Network(CGAN)based anti-interference recognition method for welding images.The generator adopts an improved U-Net++structure,adds a Multi-scale Channel Attention module(MS-CAM),introduces Deep Supervision,and proposes a Multi-output Fusion strategy(MOFS)in the output result to en-hance the image inpainting effect;the discriminator uses PatchGAN.The center of the laser stripe is obtained using the grayscale center of mass method and then combined with polynomial fitting to extract the feature points of the weld seam.The experimental results show that the PSNR of the inpainting image is 26.24 dB,the SSIM is 0.98,and the LPIPS is 0.032.The centerline of the inpainting image and the centerline of the noise-free image laser stripe are fitted with a curve.The error of centerline feature points is no more than 5%,confirming the superiority and feasibility of the method.
