The spin crossover（SCO） compound [Fe（bapbpy）（NCS）2],where bapbpy contains two fused N,N-bis（2-pyridyl）amines,has been studied by DFT/TD-DFT/BS-DFT methods.Several density functionals and basis sets were used i...The spin crossover（SCO） compound [Fe（bapbpy）（NCS）2],where bapbpy contains two fused N,N-bis（2-pyridyl）amines,has been studied by DFT/TD-DFT/BS-DFT methods.Several density functionals and basis sets were used in the calculation to obtain optimized geometries of the compound in the low-（LS） and high-spin（HS） states.The vibrational modes and IR spectra,spin splitting energies,excited states and UV/Vis absorption spectra were obtained.The structural parameters of the calculated isolated complex are in good agreement with the X-ray data.We investigate three dimers of [Fe（bapbpy）（NCS）2] complex for their magnetic properties.It has been found that the complex（1,3） has ferromagnetic character while the others are antiferromagnetic in nature by using a broken symmetry approach in the DFT framework（BS-DFT） with support from the coupling constant values（J） and spin density plots.展开更多
The measure J in J value segmentation (JSEG) fails to represent the discontinuity of color, which degrades the robustness and discrimination of JSEG. An improved approach for JSEG algorithm was proposed for unsupervis...The measure J in J value segmentation (JSEG) fails to represent the discontinuity of color, which degrades the robustness and discrimination of JSEG. An improved approach for JSEG algorithm was proposed for unsupervised color-texture image segmentation. The texture and photometric invariant edge information were combined, which results in a discriminative measure for color-texture homogeneity. Based on the image whose pixel values are values of the new measure, region growing-merging algorithm used in JSEG was then employed to segment the image. Finally, experiments on a variety of real color images demonstrate performance improvement due to the proposed method.展开更多
An improved approach for JSEG is presented for unsupervised segmentation of homogeneous regions in gray-scale images. Instead of intensity quantization, an automatic classification method based on scale space-based cl...An improved approach for JSEG is presented for unsupervised segmentation of homogeneous regions in gray-scale images. Instead of intensity quantization, an automatic classification method based on scale space-based clustering is used for nonparametric clustering of image data set. Then EM algorithm with classification achieved by space-based classification scheme as initial data used to achieve Gaussian mixture modelling of image data set that is utilized for the calculation of soft J value. Original region growing algorithm is then used to segment the image based on the multiscale soft J-images. Experiments show that the new method can overcome the limitations of JSEG successfully.展开更多
基金Supported by the Natural Science Foundation of Shandong Province(No.Y2006B43)
文摘The spin crossover（SCO） compound [Fe（bapbpy）（NCS）2],where bapbpy contains two fused N,N-bis（2-pyridyl）amines,has been studied by DFT/TD-DFT/BS-DFT methods.Several density functionals and basis sets were used in the calculation to obtain optimized geometries of the compound in the low-（LS） and high-spin（HS） states.The vibrational modes and IR spectra,spin splitting energies,excited states and UV/Vis absorption spectra were obtained.The structural parameters of the calculated isolated complex are in good agreement with the X-ray data.We investigate three dimers of [Fe（bapbpy）（NCS）2] complex for their magnetic properties.It has been found that the complex（1,3） has ferromagnetic character while the others are antiferromagnetic in nature by using a broken symmetry approach in the DFT framework（BS-DFT） with support from the coupling constant values（J） and spin density plots.
基金The National Natural Science Foundation of China (No. 60675023)
文摘The measure J in J value segmentation (JSEG) fails to represent the discontinuity of color, which degrades the robustness and discrimination of JSEG. An improved approach for JSEG algorithm was proposed for unsupervised color-texture image segmentation. The texture and photometric invariant edge information were combined, which results in a discriminative measure for color-texture homogeneity. Based on the image whose pixel values are values of the new measure, region growing-merging algorithm used in JSEG was then employed to segment the image. Finally, experiments on a variety of real color images demonstrate performance improvement due to the proposed method.
文摘An improved approach for JSEG is presented for unsupervised segmentation of homogeneous regions in gray-scale images. Instead of intensity quantization, an automatic classification method based on scale space-based clustering is used for nonparametric clustering of image data set. Then EM algorithm with classification achieved by space-based classification scheme as initial data used to achieve Gaussian mixture modelling of image data set that is utilized for the calculation of soft J value. Original region growing algorithm is then used to segment the image based on the multiscale soft J-images. Experiments show that the new method can overcome the limitations of JSEG successfully.
