By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used bas...By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used based on neural network. A modified Hopfield network was presented for image restoration. The greed algorithm with n-simultaneous updates and apartially asynchronous algorithm were combined, im- proving convergence and avoiding synchronization penalties. Mathematical morphology was widely applicated in digital image processing. The basic idea of mathematical mor- phology is to use construction element measure image morphology for solving under- stand problem. Presented advanced Cellular neural network that forms MMCNN equa- tion to be suit for mathematical morphology filter. It gave the theory of MMCNN dynamic extent and stable state. It was evidenced that arrived mathematical morphology filter through steady of dynamic precess in definite condition. The results of implementation were applied in detecting undergroug bin level.展开更多
To troubleshoot two problems arising from the segmentation of manganese nodule images-uneven illumination and morphological defects caused by white sand coverage,we propose,with reference to features of manganese nodu...To troubleshoot two problems arising from the segmentation of manganese nodule images-uneven illumination and morphological defects caused by white sand coverage,we propose,with reference to features of manganese nodules,a method called“background gray value calculation”.As the result of the image procession with the aid this method,the two problems above are solved eventually,together with acquisition of a segmentable image of manganese nodules.As a result,its comparison with other segmentation methods justifies its feasibility and stability.Judging from simulation results,it is indicated that this method is applicable to repair the target shape in the image,and segment the manganese nodule image in a short time.Also,it could be used to synchronously process a large number of manganese nodules on different conditions in an image,laying a good foundation for automatic underwater manganese nodule survey.Even if the target in the image is slightly distorted,the statistical data of manganese nodules are still accurate.Moreover,other methods cannot be fully applied to the segmentation of manganese nodule images;in another word,the effectiveness and stability of this method are proved.展开更多
文摘By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used based on neural network. A modified Hopfield network was presented for image restoration. The greed algorithm with n-simultaneous updates and apartially asynchronous algorithm were combined, im- proving convergence and avoiding synchronization penalties. Mathematical morphology was widely applicated in digital image processing. The basic idea of mathematical mor- phology is to use construction element measure image morphology for solving under- stand problem. Presented advanced Cellular neural network that forms MMCNN equa- tion to be suit for mathematical morphology filter. It gave the theory of MMCNN dynamic extent and stable state. It was evidenced that arrived mathematical morphology filter through steady of dynamic precess in definite condition. The results of implementation were applied in detecting undergroug bin level.
基金This work and Mao were supported by Open Fund Project of China Key Laboratory of Submarine Geoscience(KLSG1802)Science&Technology Project of China Ocean Mineral Resources Research and Development Association(DY135-N1-1-05)Science&Technology Project of Zhoushan city of Zhejiang Province(2019C42271,2019C33205).
文摘To troubleshoot two problems arising from the segmentation of manganese nodule images-uneven illumination and morphological defects caused by white sand coverage,we propose,with reference to features of manganese nodules,a method called“background gray value calculation”.As the result of the image procession with the aid this method,the two problems above are solved eventually,together with acquisition of a segmentable image of manganese nodules.As a result,its comparison with other segmentation methods justifies its feasibility and stability.Judging from simulation results,it is indicated that this method is applicable to repair the target shape in the image,and segment the manganese nodule image in a short time.Also,it could be used to synchronously process a large number of manganese nodules on different conditions in an image,laying a good foundation for automatic underwater manganese nodule survey.Even if the target in the image is slightly distorted,the statistical data of manganese nodules are still accurate.Moreover,other methods cannot be fully applied to the segmentation of manganese nodule images;in another word,the effectiveness and stability of this method are proved.
