In this paper, the Kalman filter is used to predict image feature positionaround which an image-processing window is then established to diminish feature-searching area andto heighten the image-processing speed. Accor...In this paper, the Kalman filter is used to predict image feature positionaround which an image-processing window is then established to diminish feature-searching area andto heighten the image-processing speed. According to the fundamentals of image-based visual servoing(IBVS), the cerebellar model articulation controller (CMAC) neural network is inserted into thevisual servo control loop to implement the nonlinear mapping from the error signal in the imagespace to the control signal in the input space instead of the iterative adjustment and complicatedinverse solution of the image Jacobian. Simulation results show that the feature point can bepredicted efficiently using the Kalman filter and on-line supervised learning can be realized usingCMAC neural network; end-effector can track the target object very well.展开更多
Surface small defects are often missed and incorrectly detected due to their small quantity and unapparent visual features.A method named CSYOLOv3,which is based on CutMix and YOLOv3,is proposed to solve such a proble...Surface small defects are often missed and incorrectly detected due to their small quantity and unapparent visual features.A method named CSYOLOv3,which is based on CutMix and YOLOv3,is proposed to solve such a problem.First,a four-image CutMix method is used to increase the small-defect quantity,and the process is dynamically adjusted based on the beta distribution.Then,the classic YOLOv3 is improved to detect small defects accurately.The shallow and large feature maps are split,and several of them are merged with the feature maps of the predicted branch to preserve the shallow features.The loss function of YOLOv3 is optimized and weighted to improve the attention to small defects.Finally,this method is used to detect 512×512 pixel images under RTX 2060Ti GPU,which can reach the speed of 14.09 frame/s,and the mAP is 71.80%,which is 5%-10%higher than that of other methods.For small defects below 64×64 pixels,the mAP of the method reaches 64.15%,which is 14%higher than that of YOLOv3-GIoU.The surface defects of the workpiece can be effectively detected by the proposed method,and the performance in detecting small defects is significantly improved.展开更多
According to the characteristics of dynamic firing in pulse coupled neural network (PCNN) and regional configuration in retinal blood vessel network, a new method combined with simplified PCNN and fast 2D-Otsu algorit...According to the characteristics of dynamic firing in pulse coupled neural network (PCNN) and regional configuration in retinal blood vessel network, a new method combined with simplified PCNN and fast 2D-Otsu algorithm was proposed for automated retinal blood vessels segmentation. Firstly, 2D Gaussian matched filter was used to enhance the retinal images and simplified PCNN was employed to segment the blood vessels by firing neighborhood neurons. Then, fast 2D-Otsu algorithm was introduced to search the best segmentation results and iteration times with less computation time. Finally, the whole vessel network was obtained via analyzing the regional connectivity. Experiments implemented on the public Hoover database indicate that this new method gets a 0.803 5 true positive rate and a 0.028 0 false positive rate on an average. According to the test results, compared with Hoover algorithm and method of PCNN and 1D-Otsu, the proposed method shows much better performance.展开更多
The cellular neural/nonlinear network （CNN） is a powerful tool for image and video signal processing, robotic and biological visions. This paper introduces a kind of CNNs with performance of extracting closed domain...The cellular neural/nonlinear network （CNN） is a powerful tool for image and video signal processing, robotic and biological visions. This paper introduces a kind of CNNs with performance of extracting closed domains in binary images, and gives a general method for designing templates of such a kind of CNNs. One theorem provides parameter inequalities for determining parameter intervals for implementing prescribed image processing functions, respectively. Examples for extracting closed domains in binary scale images are given.展开更多
Objective To develop and evaluate the rat model of chronic glaucoma by episcleral veins ligation （EVL）. Methods Experimental glaucoma was induced unilaterally in 28 male Sprague-Dawley rats by ligating two episclera...Objective To develop and evaluate the rat model of chronic glaucoma by episcleral veins ligation （EVL）. Methods Experimental glaucoma was induced unilaterally in 28 male Sprague-Dawley rats by ligating two episcleral veins. Intraocular pressure （10P） in rats was measured by a Goldmann applanation tonometer under 3 % pentobarbital sodium anesthesia. The optic nerve head and retinal vasculature were assessed by repeated fundus examinations. The amount of optic nerve axons was assessed by Image-Pro Plus image analysis system in a masked fashion. Results lOP without EVL was （ 19.21 ± 1.23） mmHg, whereas the EVL eyes gained about 1.8-fold higher 10P[ （33.96 ±2. 73） mmHg]after EVL immediately （ P 〈 0. 001 ）. The elevated IOP gradually decreased over time. However, the differences were kept significant up to 8 weeks after EVL. The lOP was reduced to similar levels as contralateral eyes at 12 and 16 weeks after EVL. The glaucomatous optic nerve excavation appeared in EVL eyes at 8 weeks after EVL, and the optic nerve excavation enlarged gradually with the increasing post-operation time. The amount of optic nerve axons also significantly decreased in EVL eyes at 8 weeks after EVL, and the amount of axons decreased gradually with the increasing post-operation time. Conclusion Increase of lOP caused by EVL represents a useful and efficient model of experimental glaucoma in rats.展开更多
基金The National Natural Science Foundation of China (59990470).
文摘In this paper, the Kalman filter is used to predict image feature positionaround which an image-processing window is then established to diminish feature-searching area andto heighten the image-processing speed. According to the fundamentals of image-based visual servoing(IBVS), the cerebellar model articulation controller (CMAC) neural network is inserted into thevisual servo control loop to implement the nonlinear mapping from the error signal in the imagespace to the control signal in the input space instead of the iterative adjustment and complicatedinverse solution of the image Jacobian. Simulation results show that the feature point can bepredicted efficiently using the Kalman filter and on-line supervised learning can be realized usingCMAC neural network; end-effector can track the target object very well.
基金The National Natural Science Foundation of China(No.52075095).
文摘Surface small defects are often missed and incorrectly detected due to their small quantity and unapparent visual features.A method named CSYOLOv3,which is based on CutMix and YOLOv3,is proposed to solve such a problem.First,a four-image CutMix method is used to increase the small-defect quantity,and the process is dynamically adjusted based on the beta distribution.Then,the classic YOLOv3 is improved to detect small defects accurately.The shallow and large feature maps are split,and several of them are merged with the feature maps of the predicted branch to preserve the shallow features.The loss function of YOLOv3 is optimized and weighted to improve the attention to small defects.Finally,this method is used to detect 512×512 pixel images under RTX 2060Ti GPU,which can reach the speed of 14.09 frame/s,and the mAP is 71.80%,which is 5%-10%higher than that of other methods.For small defects below 64×64 pixels,the mAP of the method reaches 64.15%,which is 14%higher than that of YOLOv3-GIoU.The surface defects of the workpiece can be effectively detected by the proposed method,and the performance in detecting small defects is significantly improved.
基金Project (60872081) supported by the National Natural Science Foundation of ChinaProject (50051) supported by the Program for New Century Excellent Talents in UniversityProject (4092034) supported by the Natural Science Foundation of Beijing
文摘According to the characteristics of dynamic firing in pulse coupled neural network (PCNN) and regional configuration in retinal blood vessel network, a new method combined with simplified PCNN and fast 2D-Otsu algorithm was proposed for automated retinal blood vessels segmentation. Firstly, 2D Gaussian matched filter was used to enhance the retinal images and simplified PCNN was employed to segment the blood vessels by firing neighborhood neurons. Then, fast 2D-Otsu algorithm was introduced to search the best segmentation results and iteration times with less computation time. Finally, the whole vessel network was obtained via analyzing the regional connectivity. Experiments implemented on the public Hoover database indicate that this new method gets a 0.803 5 true positive rate and a 0.028 0 false positive rate on an average. According to the test results, compared with Hoover algorithm and method of PCNN and 1D-Otsu, the proposed method shows much better performance.
基金The project supported by National Natural Science Foundation of China under Grant No. 70271068, the Foundation for University Key Teachers, and the Research Fund for the Doctoral Program of Higher Education of the Ministry of Education of China under Grant No. 200200080004
文摘The cellular neural/nonlinear network （CNN） is a powerful tool for image and video signal processing, robotic and biological visions. This paper introduces a kind of CNNs with performance of extracting closed domains in binary images, and gives a general method for designing templates of such a kind of CNNs. One theorem provides parameter inequalities for determining parameter intervals for implementing prescribed image processing functions, respectively. Examples for extracting closed domains in binary scale images are given.
基金Supported by Shanghai Education Committee Project Foundation (06BZ040)
文摘Objective To develop and evaluate the rat model of chronic glaucoma by episcleral veins ligation （EVL）. Methods Experimental glaucoma was induced unilaterally in 28 male Sprague-Dawley rats by ligating two episcleral veins. Intraocular pressure （10P） in rats was measured by a Goldmann applanation tonometer under 3 % pentobarbital sodium anesthesia. The optic nerve head and retinal vasculature were assessed by repeated fundus examinations. The amount of optic nerve axons was assessed by Image-Pro Plus image analysis system in a masked fashion. Results lOP without EVL was （ 19.21 ± 1.23） mmHg, whereas the EVL eyes gained about 1.8-fold higher 10P[ （33.96 ±2. 73） mmHg]after EVL immediately （ P 〈 0. 001 ）. The elevated IOP gradually decreased over time. However, the differences were kept significant up to 8 weeks after EVL. The lOP was reduced to similar levels as contralateral eyes at 12 and 16 weeks after EVL. The glaucomatous optic nerve excavation appeared in EVL eyes at 8 weeks after EVL, and the optic nerve excavation enlarged gradually with the increasing post-operation time. The amount of optic nerve axons also significantly decreased in EVL eyes at 8 weeks after EVL, and the amount of axons decreased gradually with the increasing post-operation time. Conclusion Increase of lOP caused by EVL represents a useful and efficient model of experimental glaucoma in rats.
