With the continuous development of the economy and society,plastic pollution in rivers,lakes,oceans,and other bodies of water is increasingly severe,posing a serious challenge to underwater ecosystems.Effective cleani...With the continuous development of the economy and society,plastic pollution in rivers,lakes,oceans,and other bodies of water is increasingly severe,posing a serious challenge to underwater ecosystems.Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste.However,it often causes significant challenges such as noise interference,low contrast,and blurred textures in underwater optical images.A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed,which combines weighted logarithmic transformations,adaptive gamma correction,improved multi-scale Retinex(MSR)algorithm,and the contrast limited adaptive histogram equalization(CLAHE)algorithm.The proposed algorithm improves brightness,contrast,and color recovery and enhances detail features resulting in better overall image quality.A network framework is proposed in this article based on the YOLOv5 model.MobileViT is used as the backbone of the network framework,detection layer is added to improve the detection capability for small targets,self-attention and mixed-attention modules are introduced to enhance the recognition capability of important features.The cross stage partial(CSP)structure is employed in the spatial pyramid pooling(SPP)section to enrich feature information,and the complete intersection over union(CIOU)loss is replaced with the focal efficient intersection over union(EIOU)loss to accelerate convergence while improving regression accuracy.Experimental results proved that the target recognition algorithm achieved a recognition accuracy of 0.913 and ensured a recognition speed of 45.56 fps/s.Subsequently,Using red,green,blue and depth(RGB-D)camera to construct a system for identifying and locating underwater plastic waste.Experiments were conducted underwater for recognition,localization,and error analysis.The experimental results demonstrate the effectiveness of the proposed method for identifying and locating underwater plastic waste,and it has good locali展开更多
In this study,underwater explosion tests with 2.5 g trinitrotoluene explosive under different fixed plates with prefabricated holes were conducted.The experimental results showed that the air inflow from the prefabric...In this study,underwater explosion tests with 2.5 g trinitrotoluene explosive under different fixed plates with prefabricated holes were conducted.The experimental results showed that the air inflow from the prefabricated hole caused the bubble to collapse earlier with an increase in the hole diameter.In addition,the deformation mode of the thin plate transitioned from“convex”to“concave”(up to down).Next,the coupled Eulerian-Lagrangian method was used to perform the corresponding numerical simulation.The accuracy of the numerical simulation method was verified through a comparison with the experimental data.In addition,a series of numerical simulations were conducted with different prefabricated-hole diameters,blast distances,and prefabricated-hole shapes.The results showed that the bubble-pulsating water jet substantially influenced the deformation of the thin plate when the diameter of the prefabricated hole was within the theoretical maximum bubble radius.When the blast distance was within the theoretical maximum bubble radius,the thin plate was subjected to only a single bubble pulsation owing to the air inflow from the prefabricated hole.展开更多
水下光学成像是重要的水下探测方式。现有水下相机成像检测方法受到水体本身以及测量方法的影响,难以准确进行成像分辨率检测。提出了基于水下平行光管的水下相机成像分辨率检测技术,通过在水中产生平行光束,直接对水下相机成像分辨率...水下光学成像是重要的水下探测方式。现有水下相机成像检测方法受到水体本身以及测量方法的影响,难以准确进行成像分辨率检测。提出了基于水下平行光管的水下相机成像分辨率检测技术,通过在水中产生平行光束,直接对水下相机成像分辨率进行检测。通过仿真得出:水下平行光管在水中可见光和空气中单波长的调制传递函数(Modulation Transfer Function, MTF)基本一致。利用这一结论,提出了水下平行光管空气中装调检测的方法。针对实验室所研制的一款水下相机开展实验测试,其在水中可见光与空气中635 m光源照明条件下的分辨率相同。实验结果表明,所提出的基于水下平行光管的水下相机成像分辨率检测方法可有效消除水体对分辨率测量的影响,实现水下相机成像分辨率的准确测量。展开更多
Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior(ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of wat...Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior(ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of water. Due to mass refraction of light in the process of underwater imaging, fog effects would lead to image blurring. And color cast is closely related to different degree of attenuation while light with different wavelengths is traveling in water. The proposed method here integrates the ISDCP and quantitative histogram stretching techniques into the image enhancement procedure. Firstly, the threshold value is set during the refinement process of the transmission maps to identify the original mismatching, and to conduct the differentiated defogging process further. Secondly, a method of judging the propagating distance of light is adopted to get the attenuation degree of energy during the propagation underwater. Finally, the image histogram is stretched quantitatively in Red-Green-Blue channel respectively according to the degree of attenuation in each color channel. The proposed method ISDCP can reduce the computational complexity and improve the efficiency in terms of defogging effect to meet the real-time requirements. Qualitative and quantitative comparison for several different underwater scenes reveals that the proposed method can significantly improve the visibility compared with previous methods.展开更多
基金supported by the Foundation of Henan Key Laboratory of Underwater Intelligent Equipment under Grant No.KL02C2105Project of SongShan Laboratory under Grant No.YYJC062022012+2 种基金Training Plan for Young Backbone Teachers in Colleges and Universities in Henan Province under Grant No.2021GGJS077Key Scientific Research Projects of Colleges and Universities in Henan Province under Grant No.22A460022North China University of Water Resources and Electric Power Young Backbone Teacher Training Project under Grant No.2021-125-4.
文摘With the continuous development of the economy and society,plastic pollution in rivers,lakes,oceans,and other bodies of water is increasingly severe,posing a serious challenge to underwater ecosystems.Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste.However,it often causes significant challenges such as noise interference,low contrast,and blurred textures in underwater optical images.A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed,which combines weighted logarithmic transformations,adaptive gamma correction,improved multi-scale Retinex(MSR)algorithm,and the contrast limited adaptive histogram equalization(CLAHE)algorithm.The proposed algorithm improves brightness,contrast,and color recovery and enhances detail features resulting in better overall image quality.A network framework is proposed in this article based on the YOLOv5 model.MobileViT is used as the backbone of the network framework,detection layer is added to improve the detection capability for small targets,self-attention and mixed-attention modules are introduced to enhance the recognition capability of important features.The cross stage partial(CSP)structure is employed in the spatial pyramid pooling(SPP)section to enrich feature information,and the complete intersection over union(CIOU)loss is replaced with the focal efficient intersection over union(EIOU)loss to accelerate convergence while improving regression accuracy.Experimental results proved that the target recognition algorithm achieved a recognition accuracy of 0.913 and ensured a recognition speed of 45.56 fps/s.Subsequently,Using red,green,blue and depth(RGB-D)camera to construct a system for identifying and locating underwater plastic waste.Experiments were conducted underwater for recognition,localization,and error analysis.The experimental results demonstrate the effectiveness of the proposed method for identifying and locating underwater plastic waste,and it has good locali
基金supported by the National Natural Science Foundation of China(Grant No.12172178).
文摘In this study,underwater explosion tests with 2.5 g trinitrotoluene explosive under different fixed plates with prefabricated holes were conducted.The experimental results showed that the air inflow from the prefabricated hole caused the bubble to collapse earlier with an increase in the hole diameter.In addition,the deformation mode of the thin plate transitioned from“convex”to“concave”(up to down).Next,the coupled Eulerian-Lagrangian method was used to perform the corresponding numerical simulation.The accuracy of the numerical simulation method was verified through a comparison with the experimental data.In addition,a series of numerical simulations were conducted with different prefabricated-hole diameters,blast distances,and prefabricated-hole shapes.The results showed that the bubble-pulsating water jet substantially influenced the deformation of the thin plate when the diameter of the prefabricated hole was within the theoretical maximum bubble radius.When the blast distance was within the theoretical maximum bubble radius,the thin plate was subjected to only a single bubble pulsation owing to the air inflow from the prefabricated hole.
文摘水下光学成像是重要的水下探测方式。现有水下相机成像检测方法受到水体本身以及测量方法的影响,难以准确进行成像分辨率检测。提出了基于水下平行光管的水下相机成像分辨率检测技术,通过在水中产生平行光束,直接对水下相机成像分辨率进行检测。通过仿真得出:水下平行光管在水中可见光和空气中单波长的调制传递函数(Modulation Transfer Function, MTF)基本一致。利用这一结论,提出了水下平行光管空气中装调检测的方法。针对实验室所研制的一款水下相机开展实验测试,其在水中可见光与空气中635 m光源照明条件下的分辨率相同。实验结果表明,所提出的基于水下平行光管的水下相机成像分辨率检测方法可有效消除水体对分辨率测量的影响,实现水下相机成像分辨率的准确测量。
基金supported by the National Natural Science Foundation of China (No. 61401413)
文摘Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior(ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of water. Due to mass refraction of light in the process of underwater imaging, fog effects would lead to image blurring. And color cast is closely related to different degree of attenuation while light with different wavelengths is traveling in water. The proposed method here integrates the ISDCP and quantitative histogram stretching techniques into the image enhancement procedure. Firstly, the threshold value is set during the refinement process of the transmission maps to identify the original mismatching, and to conduct the differentiated defogging process further. Secondly, a method of judging the propagating distance of light is adopted to get the attenuation degree of energy during the propagation underwater. Finally, the image histogram is stretched quantitatively in Red-Green-Blue channel respectively according to the degree of attenuation in each color channel. The proposed method ISDCP can reduce the computational complexity and improve the efficiency in terms of defogging effect to meet the real-time requirements. Qualitative and quantitative comparison for several different underwater scenes reveals that the proposed method can significantly improve the visibility compared with previous methods.
