Shape skeletonization （i.e., medial axis extraction） is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. In this paper, the authors expan...Shape skeletonization （i.e., medial axis extraction） is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. In this paper, the authors expand the use of diffusion equations combined with distance field information to approximate medial axes of arbitrary 3D differential properties. It offers an alternative solids represented by polygonal meshes based on their but natural way for medial axis extraction for commonly used 3D polygonal models. By solving the PDE along time axis, this system can not only quickly extract diffusion-based medial axes of input meshes, but also allow users to visualize the extraction process at each time step. In addition, the proposed model provides users a set of manipulation toolkits to sculpt extracted medial axes, then use diffusion-based techniques to recover corresponding deformed shapes according to the original input datasets. This skeleton-based shape manipulation offers a fast and easy way for animation and deformation of complicated mesh objects.展开更多
Detection navigation baseline is primary for the automation of maize weeder in seedling.In the navigation technology based on machine vision,maize seeding or weed near the camera is photographed as a discrete area,whi...Detection navigation baseline is primary for the automation of maize weeder in seedling.In the navigation technology based on machine vision,maize seeding or weed near the camera is photographed as a discrete area,while a plant far away from the camera is photographed as a strip area along with other plants in the same row.The two problems cannot be solved by one method.However,in this paper,an algorithm of detection navigation baseline in the row-following operation of maize weeder based on axis extraction was proposed to solve the both problems.Firstly,plants are distinguished from the background based on color feature,and the binary image is acquired.Secondly,plants are described as a set of connected components with numbers after connected components labeling and noise clearing.Thirdly,the axes of all connected components are extracted according to the calculation method of rotary inertia in physics.Next,the abnormal connected components with axes are deleted because the angles between the axes and X-axis are above angle threshold.Then,the judgment model is built based on angle tolerance and distance tolerance,the connected components in a same row based on this model through two-step traversal are merged,and a new axis is re-extracted as the axis of the plant row.Finally,the navigation baselines are detected based on the axes of the plant row.The experimental results show that the accuracy of this algorithm is more than 93%,and the computing time is less than 1.6 s,which can meet the accuracy and real-time performance requirements of maize weeder.展开更多
基金This research was supported in part by the National Science Foundation (NSF) Information Technology Research under Grant No.IIS-0082035the NSF under Grant No.IIS-0097646+1 种基金Alfred P.Sloan Fellowship,Honda Initiation Awardan appointment of Haixia Du to the NLM Research Participation Program sponsored by the National Library of Medicine and administered by the Oak Ridge Institute for Science and Education
文摘Shape skeletonization （i.e., medial axis extraction） is powerful in many visual computing applications, such as pattern recognition, object segmentation, registration, and animation. In this paper, the authors expand the use of diffusion equations combined with distance field information to approximate medial axes of arbitrary 3D differential properties. It offers an alternative solids represented by polygonal meshes based on their but natural way for medial axis extraction for commonly used 3D polygonal models. By solving the PDE along time axis, this system can not only quickly extract diffusion-based medial axes of input meshes, but also allow users to visualize the extraction process at each time step. In addition, the proposed model provides users a set of manipulation toolkits to sculpt extracted medial axes, then use diffusion-based techniques to recover corresponding deformed shapes according to the original input datasets. This skeleton-based shape manipulation offers a fast and easy way for animation and deformation of complicated mesh objects.
基金This work was supported by National Key Research and Development Program of China(2017YED0701500)Shanxi Provincial Program for Youth Science and Technology(201801D221289)Shanxi Agriculture University Youth Science and Technology Innovation Project(J141802199).
文摘Detection navigation baseline is primary for the automation of maize weeder in seedling.In the navigation technology based on machine vision,maize seeding or weed near the camera is photographed as a discrete area,while a plant far away from the camera is photographed as a strip area along with other plants in the same row.The two problems cannot be solved by one method.However,in this paper,an algorithm of detection navigation baseline in the row-following operation of maize weeder based on axis extraction was proposed to solve the both problems.Firstly,plants are distinguished from the background based on color feature,and the binary image is acquired.Secondly,plants are described as a set of connected components with numbers after connected components labeling and noise clearing.Thirdly,the axes of all connected components are extracted according to the calculation method of rotary inertia in physics.Next,the abnormal connected components with axes are deleted because the angles between the axes and X-axis are above angle threshold.Then,the judgment model is built based on angle tolerance and distance tolerance,the connected components in a same row based on this model through two-step traversal are merged,and a new axis is re-extracted as the axis of the plant row.Finally,the navigation baselines are detected based on the axes of the plant row.The experimental results show that the accuracy of this algorithm is more than 93%,and the computing time is less than 1.6 s,which can meet the accuracy and real-time performance requirements of maize weeder.
