Proper parameters for image taking and minimum field number for image processing were investigated to evaluate volume fraction of unhydrated cement（UHC） in both neat cement paste and slag blended cement paste. Our r...Proper parameters for image taking and minimum field number for image processing were investigated to evaluate volume fraction of unhydrated cement（UHC） in both neat cement paste and slag blended cement paste. Our research suggested that magnification 250x was sufficient for the two pastes, and accelerating voltage should be set as 15 kV and 20 kV for BSE image taking of neat cement paste and slag blended cement paste respectively; the minimum field number increased while the total imaging area stayed the same as the magnification increased within certain statistical bias.展开更多
This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to m...This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to make image segmentation. Compared to methods based on level set, the proposed DRC method has some advantages for tablet packaging image segmentation. The local re- gional control term and the rectangle initialization contour are first employed in this method to quickly segment un- even grayscale images and accelerate the curve evolution rate. Gaussian filter operator and the convolution calcula- tion are then adopted to remove the effects of texture noises in image segmentation. The developed penalty energy function, as regularization term, increases the constrained conditions based on the gradient flow conditions. Since the potential function is embedded into the level set of evo- lution equations and the image contour evolutions are bi- laterally extended, the proposed method further improves the accuracy of image contours. Experimental studies show that the DRC method greatly improves the computational efficiency and numerical accuracy, and achieves better results for image contour segmentation compared to other level set methods.展开更多
基金Funded by the Major State Basic Research Development Program of China(973 Program)(No.2009CB623104)
文摘Proper parameters for image taking and minimum field number for image processing were investigated to evaluate volume fraction of unhydrated cement（UHC） in both neat cement paste and slag blended cement paste. Our research suggested that magnification 250x was sufficient for the two pastes, and accelerating voltage should be set as 15 kV and 20 kV for BSE image taking of neat cement paste and slag blended cement paste respectively; the minimum field number increased while the total imaging area stayed the same as the magnification increased within certain statistical bias.
基金the Science and Technology Commission of Shanghai Municipality(Grant No.14YF1408600)the Shanghai Municipal Commission of Economy and Informatization under Shanghai Industry University Research Collaboration(Grant No.CXY-2013-71)+2 种基金the Natural Science Foundation of Shandong Province(Grant No.ZR2012FM008)the Science and Technology Development Program of Shandong Province(Grant No.2013GNC11012)the National Natural Science Foundation of China(Grant No.61100115)
文摘This paper proposes a novel double regular- ization control （DRC） method which is used for tablet packaging image segmentation. Since the intensities of tablet packaging images are inhomogenous, it is difficult to make image segmentation. Compared to methods based on level set, the proposed DRC method has some advantages for tablet packaging image segmentation. The local re- gional control term and the rectangle initialization contour are first employed in this method to quickly segment un- even grayscale images and accelerate the curve evolution rate. Gaussian filter operator and the convolution calcula- tion are then adopted to remove the effects of texture noises in image segmentation. The developed penalty energy function, as regularization term, increases the constrained conditions based on the gradient flow conditions. Since the potential function is embedded into the level set of evo- lution equations and the image contour evolutions are bi- laterally extended, the proposed method further improves the accuracy of image contours. Experimental studies show that the DRC method greatly improves the computational efficiency and numerical accuracy, and achieves better results for image contour segmentation compared to other level set methods.
