A new stereo matching scheme from image pairs based on graph cuts is given,which can solve the problem of large color differences as the result of fusing matching results of graph cuts from different color spaces.This...A new stereo matching scheme from image pairs based on graph cuts is given,which can solve the problem of large color differences as the result of fusing matching results of graph cuts from different color spaces.This scheme builds normalized histogram and reference histogram from matching results,and uses clustering algorithm to process the two histograms.Region histogram statistical method is adopted to retrieve depth data to achieve final matching results.Regular stereo matching library is used to verify this scheme,and experiments reported in this paper support availability of this method for automatic image processing.This scheme renounces the step of manual selection for adaptive color space and can obtain stable matching results.The whole procedure can be executed automatically and improve the integration level of image analysis process.展开更多
To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy ap...To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.展开更多
基金Sponsored by"985"Second Procession Construction of Ministry of Education(3040012040101)
文摘A new stereo matching scheme from image pairs based on graph cuts is given,which can solve the problem of large color differences as the result of fusing matching results of graph cuts from different color spaces.This scheme builds normalized histogram and reference histogram from matching results,and uses clustering algorithm to process the two histograms.Region histogram statistical method is adopted to retrieve depth data to achieve final matching results.Regular stereo matching library is used to verify this scheme,and experiments reported in this paper support availability of this method for automatic image processing.This scheme renounces the step of manual selection for adaptive color space and can obtain stable matching results.The whole procedure can be executed automatically and improve the integration level of image analysis process.
基金supported by the Natural Science Foundation of Shandong Province (Y2006A12)the Scientific Research Development Project of Shandong Provincial Education Department (J06P01)+2 种基金the Science and Technology Foundation of Universityof Jinan (XKY0808 XKY0703)the Doctoral Foundation of University of Jinan (B0633).
文摘To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.