In this study,an image binarization optimization algorithm,based on local threshold algorithms,is proposed because global and traditional local threshold segmentation algorithms cannot effectively address the problems...In this study,an image binarization optimization algorithm,based on local threshold algorithms,is proposed because global and traditional local threshold segmentation algorithms cannot effectively address the problems of nonuniform backgrounds of wood defect images.The proposed algorithm calculates the threshold by the mean,standard deviation and the extreme value of the window.The results indicate that this modified algorithm enhances the image segmentation for wood defect images on a complex background,which is much superior to the global threshold algorithm and the Bernsen algorithm,and slightly better than the Niblack algorithm and Sauvola algorithm.Compared with similar models,the algorithm proposed in this paper has higher segmentation accuracy,as high as 92.6%for wood defect images with a complex background.展开更多
Image segmentation is a key and fundamental problem in image processing,computer graphics,and computer vision.Level set based method for image segmentation is used widely for its topology flexibility and proper mathem...Image segmentation is a key and fundamental problem in image processing,computer graphics,and computer vision.Level set based method for image segmentation is used widely for its topology flexibility and proper mathematical formulation.However,poor performance of existing level set models on noisy images and weak boundary limit its application in image segmentation.In this paper,we present a region consistency constraint term to measure the regional consistency on both sides of the boundary,this term defines the boundary of the image within a range,and hence increases the stability of the level set model.The term can make existing level set models significantly improve the efficiency of the algorithms on segmenting images with noise and weak boundary.Furthermore,this constraint term can make edge-based level set model overcome the defect of sensitivity to the initial contour.The experimental results show that our algorithm is efficient for image segmentation and outperform the existing state-of-art methods regarding images with noise and weak boundary.展开更多
The uniform ring model and the shell-spring model for segmental lining design are reviewed in thisarticle. The former is the most promising means to reflect the real behavior of segmental lining, while thelatter is th...The uniform ring model and the shell-spring model for segmental lining design are reviewed in thisarticle. The former is the most promising means to reflect the real behavior of segmental lining, while thelatter is the most popular means in practice due to its simplicity. To understand the relationship and thedifference between these two models, both of them are applied to the engineering practice of FuzhouMetro Line I, where the key parameters used in both models are described and compared. The effectiveratio of bending rigidity h reflecting the relative stiffness between segmental lining and surroundingground and the transfer ratio of bending moment x reflecting the relative stiffness between segment andjoint, which are two key parameters used in the uniform ring model, are especially emphasized. Thereasonable values for these two key parameters are calibrated by comparing the bending momentscalculated from both two models. Through case studies, it is concluded that the effective ratio of bendingrigidity h increases significantly with good soil properties, increases slightly with increasing overburden,and decreases slightly with increasing water head. Meanwhile, the transfer ratio of bending moment xseems to only relate to the properties of segmental lining itself and has a minor relation with the groundconditions. These results could facilitate the design practice for Fuzhou Metro Line I, and could alsoprovide some references to other projects with respect to similar scenarios.展开更多
Pulse-coupled neural network （PCNN） is a novel neural network, which has been widely used in image segmentation. However, there are still some limitations, such as trial-and-error parameter settings and manual selec...Pulse-coupled neural network （PCNN） is a novel neural network, which has been widely used in image segmentation. However, there are still some limitations, such as trial-and-error parameter settings and manual selection of the optimal results. This paper puts forward a new method based on the simplified PCNN model for automatic image segmentation. By calculating the un- iformity measure of the corresponding image at each process of iteration, the optimal segmentation result is obtained when the max- imum value of the uniformity measure is achieved. Experimental results show that the proposed method can automatically achieve better segmentation result and has a common adaptability.展开更多
Spatial data uncertainty can directly affect the quality of digital products and GIS-based decision making. On the basis of the characteristics of randomicity of positional data and fuzziness of attribute data, taking...Spatial data uncertainty can directly affect the quality of digital products and GIS-based decision making. On the basis of the characteristics of randomicity of positional data and fuzziness of attribute data, taking entropy as a measure, the stochastic entropy model of positional data uncertainty and fuzzy entropy model of attribute data uncertainty are proposed. As both randomic-ity and fuzziness usually simultaneously exist in linear segments, their omnibus effects are also investigated and quantified. A novel uncertainty measure, general entropy, is presented. The general entropy can be used as a uniform measure to quantify the total un-certainty caused by stochastic uncertainty and fuzzy uncertainty in GIS.展开更多
Any undesirable signal limiting to a degree or another the integrity and the intelligibility of a useful signal can be considered as noise. In the general rule, the good performance of a system is assured only if the ...Any undesirable signal limiting to a degree or another the integrity and the intelligibility of a useful signal can be considered as noise. In the general rule, the good performance of a system is assured only if the level of power of the useful signal exceeds by several orders of magnitude that of the noise (signal to noise of a several tens of decibels). However certain elaborate methods of treatment allow working with very low signal to noise ratio in an optimal way any a priori knowledge available on the signal useful to interpret. In this work, we evaluate the robustness of the noise on a new method of multicomponent image segmentation developed recently. Two types of additional noises are considered, which are the Gaussian noise and the uniform noise, with varying correlation between the different components (or planes) of the image. Quantitative results show the influence of the noise level on the segmentation method.展开更多
基金supported by National Forestry Public Welfare Industry Scientific Research Special Subsidy Project(201304502)
文摘In this study,an image binarization optimization algorithm,based on local threshold algorithms,is proposed because global and traditional local threshold segmentation algorithms cannot effectively address the problems of nonuniform backgrounds of wood defect images.The proposed algorithm calculates the threshold by the mean,standard deviation and the extreme value of the window.The results indicate that this modified algorithm enhances the image segmentation for wood defect images on a complex background,which is much superior to the global threshold algorithm and the Bernsen algorithm,and slightly better than the Niblack algorithm and Sauvola algorithm.Compared with similar models,the algorithm proposed in this paper has higher segmentation accuracy,as high as 92.6%for wood defect images with a complex background.
基金supported in part by the NSFC-Zhejiang Joint Fund of the Integration of Informatization and Industrialization(U1609218)NSFC(61772312,61373078,61772253)+1 种基金the Key Research and Development Project of Shandong Province(2017GGX10110)NSF of Shandong Province(ZR2016FM21,ZR2016FM13)
文摘Image segmentation is a key and fundamental problem in image processing,computer graphics,and computer vision.Level set based method for image segmentation is used widely for its topology flexibility and proper mathematical formulation.However,poor performance of existing level set models on noisy images and weak boundary limit its application in image segmentation.In this paper,we present a region consistency constraint term to measure the regional consistency on both sides of the boundary,this term defines the boundary of the image within a range,and hence increases the stability of the level set model.The term can make existing level set models significantly improve the efficiency of the algorithms on segmenting images with noise and weak boundary.Furthermore,this constraint term can make edge-based level set model overcome the defect of sensitivity to the initial contour.The experimental results show that our algorithm is efficient for image segmentation and outperform the existing state-of-art methods regarding images with noise and weak boundary.
基金sponsored by the Natural Science Foundation of China(Grant No.51008082)
文摘The uniform ring model and the shell-spring model for segmental lining design are reviewed in thisarticle. The former is the most promising means to reflect the real behavior of segmental lining, while thelatter is the most popular means in practice due to its simplicity. To understand the relationship and thedifference between these two models, both of them are applied to the engineering practice of FuzhouMetro Line I, where the key parameters used in both models are described and compared. The effectiveratio of bending rigidity h reflecting the relative stiffness between segmental lining and surroundingground and the transfer ratio of bending moment x reflecting the relative stiffness between segment andjoint, which are two key parameters used in the uniform ring model, are especially emphasized. Thereasonable values for these two key parameters are calibrated by comparing the bending momentscalculated from both two models. Through case studies, it is concluded that the effective ratio of bendingrigidity h increases significantly with good soil properties, increases slightly with increasing overburden,and decreases slightly with increasing water head. Meanwhile, the transfer ratio of bending moment xseems to only relate to the properties of segmental lining itself and has a minor relation with the groundconditions. These results could facilitate the design practice for Fuzhou Metro Line I, and could alsoprovide some references to other projects with respect to similar scenarios.
文摘Pulse-coupled neural network （PCNN） is a novel neural network, which has been widely used in image segmentation. However, there are still some limitations, such as trial-and-error parameter settings and manual selection of the optimal results. This paper puts forward a new method based on the simplified PCNN model for automatic image segmentation. By calculating the un- iformity measure of the corresponding image at each process of iteration, the optimal segmentation result is obtained when the max- imum value of the uniformity measure is achieved. Experimental results show that the proposed method can automatically achieve better segmentation result and has a common adaptability.
基金Supported by the Open Research Fund Program of Geomatics and Application Laboratory, Liaoning Technical University (No.2005004).
文摘Spatial data uncertainty can directly affect the quality of digital products and GIS-based decision making. On the basis of the characteristics of randomicity of positional data and fuzziness of attribute data, taking entropy as a measure, the stochastic entropy model of positional data uncertainty and fuzzy entropy model of attribute data uncertainty are proposed. As both randomic-ity and fuzziness usually simultaneously exist in linear segments, their omnibus effects are also investigated and quantified. A novel uncertainty measure, general entropy, is presented. The general entropy can be used as a uniform measure to quantify the total un-certainty caused by stochastic uncertainty and fuzzy uncertainty in GIS.
文摘Any undesirable signal limiting to a degree or another the integrity and the intelligibility of a useful signal can be considered as noise. In the general rule, the good performance of a system is assured only if the level of power of the useful signal exceeds by several orders of magnitude that of the noise (signal to noise of a several tens of decibels). However certain elaborate methods of treatment allow working with very low signal to noise ratio in an optimal way any a priori knowledge available on the signal useful to interpret. In this work, we evaluate the robustness of the noise on a new method of multicomponent image segmentation developed recently. Two types of additional noises are considered, which are the Gaussian noise and the uniform noise, with varying correlation between the different components (or planes) of the image. Quantitative results show the influence of the noise level on the segmentation method.
