A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the chara...A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.展开更多
In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, the...In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, they are weak in suppressing background noises and worse in segmenting targets with non-uniform gray level. The concept of 2D histogram shape modification is proposed, which is realized by target information prior restraint after enhancing target information using plateau histogram equalization. The formula of 2D minimum Renyi entropy is deduced for image segmentation, then the shape-modified 2D histogram is combined wfth four optimal objective functions （i.e., maximum between-class variance, maximum entropy, maximum correlation and minimum Renyi entropy） respectively for the appli- cation of infrared image segmentation. Simultaneously, F-measure is introduced to evaluate the segmentation effects objectively. The experimental results show that F-measure is an effective evaluation index for image segmentation since its value is fully consistent with the subjective evaluation, and after 2D histogram shape modification, the methods of optimal objective functions can overcome their original forms＇ deficiency and their segmentation effects are more or less improvements, where the best one is the maximum entropy method based on 2D histogram shape modification.展开更多
In the process of 2-D compressional wave propagation in a rock mass with multiple parallel joints along the radian direction normal to the joints, the maximum possible wave amplitude corresponding to the points betwee...In the process of 2-D compressional wave propagation in a rock mass with multiple parallel joints along the radian direction normal to the joints, the maximum possible wave amplitude corresponding to the points between the two adjacent joints in the joint set is controlled by superposition of the multiple transmitted and the reflected waves, measured by the maximum rebound ratio. Parametric studies on the maximum rebound ratio along the radian direction normal to the joints were performed in universal distinct element code. The results show that the maximum rebound ratio is influenced by three factors, i.e., the normalized normal stiffness of joints, the ratio of joint spacing to wavelength and the joint from which the wave rebounds. The relationship between the maximum rebound ratio and the influence factors is generalized into five charts. Those charts can be used as the prediction model for estimating the maximum rebound ratio.展开更多
基金This project was supported by Science and Technology Research Emphasis Fund of Ministry of Education(204010) .
文摘A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.
基金supported by the China Postdoctoral Science Foundation(20100471451)the Science and Technology Foundation of State Key Laboratory of Underwater Measurement&Control Technology(9140C2603051003)
文摘In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, they are weak in suppressing background noises and worse in segmenting targets with non-uniform gray level. The concept of 2D histogram shape modification is proposed, which is realized by target information prior restraint after enhancing target information using plateau histogram equalization. The formula of 2D minimum Renyi entropy is deduced for image segmentation, then the shape-modified 2D histogram is combined wfth four optimal objective functions （i.e., maximum between-class variance, maximum entropy, maximum correlation and minimum Renyi entropy） respectively for the appli- cation of infrared image segmentation. Simultaneously, F-measure is introduced to evaluate the segmentation effects objectively. The experimental results show that F-measure is an effective evaluation index for image segmentation since its value is fully consistent with the subjective evaluation, and after 2D histogram shape modification, the methods of optimal objective functions can overcome their original forms＇ deficiency and their segmentation effects are more or less improvements, where the best one is the maximum entropy method based on 2D histogram shape modification.
基金Projects(50278057) supported by the National Natural Science Foundation of China project(2002CB412703) supported by Major State Basic Research Development Program of China
文摘In the process of 2-D compressional wave propagation in a rock mass with multiple parallel joints along the radian direction normal to the joints, the maximum possible wave amplitude corresponding to the points between the two adjacent joints in the joint set is controlled by superposition of the multiple transmitted and the reflected waves, measured by the maximum rebound ratio. Parametric studies on the maximum rebound ratio along the radian direction normal to the joints were performed in universal distinct element code. The results show that the maximum rebound ratio is influenced by three factors, i.e., the normalized normal stiffness of joints, the ratio of joint spacing to wavelength and the joint from which the wave rebounds. The relationship between the maximum rebound ratio and the influence factors is generalized into five charts. Those charts can be used as the prediction model for estimating the maximum rebound ratio.
