Fractal dimensions of a terrain quantitatively describe the self-organizedstructure of the terrain geometry. However, the local topographic variation cannot be illustrated bythe conventional box-counting method. This ...Fractal dimensions of a terrain quantitatively describe the self-organizedstructure of the terrain geometry. However, the local topographic variation cannot be illustrated bythe conventional box-counting method. This paper proposes a successive shift box-counting method,in which the studied object is divided into small sub-objects that are composed of a series of gridsaccording to its characteristic scaling. The terrain fractal dimensions in the grids are calculatedwith the successive shift box-counting method and the scattered points with values of fractaldimensions are obtained. The present research shows that the planar variation of fractal dimensionsis well consistent with fault traces and geological boundaries.展开更多
In this paper, the box-counting dimension is used to derive an explicit formula for the dimension of a fractal constructed using several contractions or by combining fractals. This dimension agrees with the Hausdorff ...In this paper, the box-counting dimension is used to derive an explicit formula for the dimension of a fractal constructed using several contractions or by combining fractals. This dimension agrees with the Hausdorff dimension in the particular case when the scales factors considered are all the same. A more general sufficient condition for the box-counting dimension and the Hausdorff dimension to be the same is given. It is also shown that the dimension of the fractal obtained by combining two fractals is the weighted average of the dimensions of the two fractals.展开更多
Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer.The present research work is useful in image processing for characterizing shape and gray-scale complexity....Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer.The present research work is useful in image processing for characterizing shape and gray-scale complexity.The proposed Modified Differential Box Counting(MDBC)extract Fractal features such as Fractal Dimension(FD),Lacunarity,and Succolarity for shape characterization.In traditional DBC method,the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels.The problem is overcome by the proposedMDBCmethod that uses box over counting and under counting that covers the whole image with required scale.In MDBC method,the suitable box size selection and Under Counting Shifting rule computation handles over counting problem.An advantage of the model is that the proposed MDBC work with recently developed methods showed that our method outperforms automatic detection and classification.The extracted features are fed to K-Nearest Neighbour(KNN)and Support Vector Machine(SVM)categorizes the mammograms into normal,benign,and malignant.The method is tested on mini MIAS datasets yields good results with improved accuracy of 93%,whereas the existing FD,GLCM,Texture and Shape feature method has 91%accuracy.展开更多
Increase in application fields of video has boosted the demand to analyze and organize video libraries for efficient scene analysis and information retrieval. This paper addresses the detection of shot transitions, wh...Increase in application fields of video has boosted the demand to analyze and organize video libraries for efficient scene analysis and information retrieval. This paper addresses the detection of shot transitions, which plays a crucial role in scene analysis, using a novel method based on fractal dimension (FD) that carries information on roughness of image intensity surface and textural structure. The proposed method is tested on sport videos including soccer and tennis matches that contain considerable amount of abrupt and gradual shot transitions. Experimental results indicate that the FD based shot transition detection method offers promising performance with respect to pixel and histogram based methods available in the literature.展开更多
A set is called regular if its Hausdorff dimension and upper box-counting dimension coincide. In this paper,we prove that the random self-conformal set is regular almost surely. Also we determine the dimensions for a ...A set is called regular if its Hausdorff dimension and upper box-counting dimension coincide. In this paper,we prove that the random self-conformal set is regular almost surely. Also we determine the dimensions for a class of random self-conformal sets.展开更多
In this paper, a quantitative analysis of the opening quality in friction spinning and its main ef-fecting factors is first made. Upon this basis the Box-Hunter’s experimental design method is usedto establish the qu...In this paper, a quantitative analysis of the opening quality in friction spinning and its main ef-fecting factors is first made. Upon this basis the Box-Hunter’s experimental design method is usedto establish the quadratic regressional equations in terms of primary opening technologicalparameters and yarn quality for medium and fine count friction spinning. The results of analysisand discussion show that the proper choice of opening roller speed and its reasonable match withthe yarn count is singificant for ensuring the spinning quality index as well as reducing unevenness,thin and thick places of the yarn.展开更多
The strength of rock structures strongly depends inter alia on surface irregularities of rock joints. These irregularities are characterized by a coefficient of joint roughness. For its estimation, visual comparison i...The strength of rock structures strongly depends inter alia on surface irregularities of rock joints. These irregularities are characterized by a coefficient of joint roughness. For its estimation, visual comparison is often used. This is rather a subjective method, therefore, fully computerized image recognition procedures were proposed. However, many of them contain imperfections, some of them even mathematical nonsenses and their application can be very dangerous in technical practice. In this paper, we recommend mathematically correct method of fully automatic estimation of the joint roughness coefficient. This method requires only the Barton profiles as a standard.展开更多
Software fault prediction is one of the most fundamental but significant management techniques in software dependability assessment. In this paper we concern the software fault prediction using a multilayer-perceptron...Software fault prediction is one of the most fundamental but significant management techniques in software dependability assessment. In this paper we concern the software fault prediction using a multilayer-perceptron neural network, where the underlying software fault count data are transformed to the Gaussian data, by means of the well-known Box-Cox power transformation. More specially, we investigate the long-term behavior of software fault counts by the neural network, and perform the multi-stage look ahead prediction of the cumulative number of software faults detected in the future software testing. In numerical examples with two actual software fault data sets, we compare our neural network approach with the existing software reliability growth models based on nonhomogeneous Poisson process, in terms of predictive performance with average relative error, and show that the data transformation employed in this paper leads to an improvement in prediction accuracy.展开更多
文摘Fractal dimensions of a terrain quantitatively describe the self-organizedstructure of the terrain geometry. However, the local topographic variation cannot be illustrated bythe conventional box-counting method. This paper proposes a successive shift box-counting method,in which the studied object is divided into small sub-objects that are composed of a series of gridsaccording to its characteristic scaling. The terrain fractal dimensions in the grids are calculatedwith the successive shift box-counting method and the scattered points with values of fractaldimensions are obtained. The present research shows that the planar variation of fractal dimensionsis well consistent with fault traces and geological boundaries.
文摘In this paper, the box-counting dimension is used to derive an explicit formula for the dimension of a fractal constructed using several contractions or by combining fractals. This dimension agrees with the Hausdorff dimension in the particular case when the scales factors considered are all the same. A more general sufficient condition for the box-counting dimension and the Hausdorff dimension to be the same is given. It is also shown that the dimension of the fractal obtained by combining two fractals is the weighted average of the dimensions of the two fractals.
文摘Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer.The present research work is useful in image processing for characterizing shape and gray-scale complexity.The proposed Modified Differential Box Counting(MDBC)extract Fractal features such as Fractal Dimension(FD),Lacunarity,and Succolarity for shape characterization.In traditional DBC method,the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels.The problem is overcome by the proposedMDBCmethod that uses box over counting and under counting that covers the whole image with required scale.In MDBC method,the suitable box size selection and Under Counting Shifting rule computation handles over counting problem.An advantage of the model is that the proposed MDBC work with recently developed methods showed that our method outperforms automatic detection and classification.The extracted features are fed to K-Nearest Neighbour(KNN)and Support Vector Machine(SVM)categorizes the mammograms into normal,benign,and malignant.The method is tested on mini MIAS datasets yields good results with improved accuracy of 93%,whereas the existing FD,GLCM,Texture and Shape feature method has 91%accuracy.
文摘Increase in application fields of video has boosted the demand to analyze and organize video libraries for efficient scene analysis and information retrieval. This paper addresses the detection of shot transitions, which plays a crucial role in scene analysis, using a novel method based on fractal dimension (FD) that carries information on roughness of image intensity surface and textural structure. The proposed method is tested on sport videos including soccer and tennis matches that contain considerable amount of abrupt and gradual shot transitions. Experimental results indicate that the FD based shot transition detection method offers promising performance with respect to pixel and histogram based methods available in the literature.
文摘A set is called regular if its Hausdorff dimension and upper box-counting dimension coincide. In this paper,we prove that the random self-conformal set is regular almost surely. Also we determine the dimensions for a class of random self-conformal sets.
文摘In this paper, a quantitative analysis of the opening quality in friction spinning and its main ef-fecting factors is first made. Upon this basis the Box-Hunter’s experimental design method is usedto establish the quadratic regressional equations in terms of primary opening technologicalparameters and yarn quality for medium and fine count friction spinning. The results of analysisand discussion show that the proper choice of opening roller speed and its reasonable match withthe yarn count is singificant for ensuring the spinning quality index as well as reducing unevenness,thin and thick places of the yarn.
基金The Project LO1202 by financial means from the Ministry of Education, Youth ； Sports under the National Sustainability Programme I
文摘The strength of rock structures strongly depends inter alia on surface irregularities of rock joints. These irregularities are characterized by a coefficient of joint roughness. For its estimation, visual comparison is often used. This is rather a subjective method, therefore, fully computerized image recognition procedures were proposed. However, many of them contain imperfections, some of them even mathematical nonsenses and their application can be very dangerous in technical practice. In this paper, we recommend mathematically correct method of fully automatic estimation of the joint roughness coefficient. This method requires only the Barton profiles as a standard.
文摘Software fault prediction is one of the most fundamental but significant management techniques in software dependability assessment. In this paper we concern the software fault prediction using a multilayer-perceptron neural network, where the underlying software fault count data are transformed to the Gaussian data, by means of the well-known Box-Cox power transformation. More specially, we investigate the long-term behavior of software fault counts by the neural network, and perform the multi-stage look ahead prediction of the cumulative number of software faults detected in the future software testing. In numerical examples with two actual software fault data sets, we compare our neural network approach with the existing software reliability growth models based on nonhomogeneous Poisson process, in terms of predictive performance with average relative error, and show that the data transformation employed in this paper leads to an improvement in prediction accuracy.
