The Experts below are selected from a list of 27 Experts worldwide ranked by ideXlab platform
Xue Anke - One of the best experts on this subject based on the ideXlab platform.
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degraded image enhancement with applications in robot vision
Systems Man and Cybernetics, 2005Co-Authors: Peng Dongliang, Xue AnkeAbstract:The theory of fuzzy sets has been used to deal with image enhancement problems for degraded images in which the image edges are uncertain and inaccurate. For those kinds of images, to some extent, the good enhancement effect can be obtained using the fuzzy sets-based image enhancement method instead of the traditional image enhancement approaches. The gray level maximum has not been changed in the classical fuzzy enhancement method proposed by S. K. Pal, so this method is not fit for the enhancement problem of degraded images with less gray levels and low contrasts; the fact that the range of membership function of gray levels is not Normalization Form, i.e. [0,1], is another disadvantage of the traditional fuzzy enhancement approach. To deal with the problems mentioned above, a generalized iterative fuzzy enhancement algorithm is proposed in this paper. A new image quality assessment criterion is suggested on the basis of the statistical features of the gray-level histogram of images to control the iterative procedure of the proposed image enhancement algorithm. Computer simulation results showed that this new enhancement method is more suitable than fuzzy enhancement and gray-level transFormation for handling the enhancement problems of images with less gray levels and low contrasts.
Peng Dong-liang - One of the best experts on this subject based on the ideXlab platform.
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SMC - Degraded image enhancement with applications in robot vision
2005 IEEE International Conference on Systems Man and Cybernetics, 1Co-Authors: Peng Dong-liangAbstract:The theory of fuzzy sets has been used to deal with image enhancement problems for degraded images in which the image edges are uncertain and inaccurate. For those kinds of images, to some extent, the good enhancement effect can be obtained using the fuzzy sets-based image enhancement method instead of the traditional image enhancement approaches. The gray level maximum has not been changed in the classical fuzzy enhancement method proposed by S. K. Pal, so this method is not fit for the enhancement problem of degraded images with less gray levels and low contrasts; the fact that the range of membership function of gray levels is not Normalization Form, i.e. [0,1], is another disadvantage of the traditional fuzzy enhancement approach. To deal with the problems mentioned above, a generalized iterative fuzzy enhancement algorithm is proposed in this paper. A new image quality assessment criterion is suggested on the basis of the statistical features of the gray-level histogram of images to control the iterative procedure of the proposed image enhancement algorithm. Computer simulation results showed that this new enhancement method is more suitable than fuzzy enhancement and gray-level transFormation for handling the enhancement problems of images with less gray levels and low contrasts.
Peng Dongliang - One of the best experts on this subject based on the ideXlab platform.
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degraded image enhancement with applications in robot vision
Systems Man and Cybernetics, 2005Co-Authors: Peng Dongliang, Xue AnkeAbstract:The theory of fuzzy sets has been used to deal with image enhancement problems for degraded images in which the image edges are uncertain and inaccurate. For those kinds of images, to some extent, the good enhancement effect can be obtained using the fuzzy sets-based image enhancement method instead of the traditional image enhancement approaches. The gray level maximum has not been changed in the classical fuzzy enhancement method proposed by S. K. Pal, so this method is not fit for the enhancement problem of degraded images with less gray levels and low contrasts; the fact that the range of membership function of gray levels is not Normalization Form, i.e. [0,1], is another disadvantage of the traditional fuzzy enhancement approach. To deal with the problems mentioned above, a generalized iterative fuzzy enhancement algorithm is proposed in this paper. A new image quality assessment criterion is suggested on the basis of the statistical features of the gray-level histogram of images to control the iterative procedure of the proposed image enhancement algorithm. Computer simulation results showed that this new enhancement method is more suitable than fuzzy enhancement and gray-level transFormation for handling the enhancement problems of images with less gray levels and low contrasts.
Qiang Yong-qian - One of the best experts on this subject based on the ideXlab platform.
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General PlatForm for Disease Computer Aided Diagnosis Based on Web
Computer Engineering, 2008Co-Authors: Qiang Yong-qianAbstract:A resolve scheme of a general platForm for disease computer-aided diagnosis based on Web is proposed,which aims at complexity and limitations of traditional medical experts system.This system and its work flow are illustrated,and the design thought and implementation method of this reslove scheme are discussed.This paper also presents the data Normalization,Form board of case,case collection,knowledge acquisition and implementation of diagnosis on line.Practical test results show that this system is feasible on both function and perFormance.
Abdul Razak Hamdan - One of the best experts on this subject based on the ideXlab platform.
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Hair-Oriented Data Model for Spatio-Temporal Data Mining
International Review on Computers and Software (IRECOS), 2015Co-Authors: Abbas Madraky, Zulaiha Ali Othman, Abdul Razak HamdanAbstract:Spatio-temporal data are complex in terms of number of attributes for spatial and temporal values, and the data are changing towards time. Traditional method to mining the spatio-temporal data is the fact that the data is stored in data warehouse in un-Normalization Form as union of spatial and temporal data know as tabular data warehouse. A Hair-Oriented Data Model (HODM) has been proved as a suitable data model for spatio-temporal data. It has reduced the file size and decreased query execution time. The spatio-temporal data stored using the HODM known as Hair-Oriented Data warehouse. However, this paper aims to presents a method to develop spatio-temporal data mining model using the Hair-Oriented data warehouse. The Hair-Oriented data model also provide with various functions for easy maintenance on spatio-temporal data warehouse. Experiment conducted using Climate-change spatio-temporal data set benchmark. Two Climate-change spatio-temporal models been developed using regression and k-nearest neighbor techniques. The perFormance of the Hair-Oriented Data Warehouse is evaluated by comparing its perFormance with traditional tabular data warehouse. The result shows that developing data mining spatio-temporal model using Hair-Oriented data warehouse is faster compare using the tabular data warehouse, therefore it can be concluded that the Hair-Oriented Data Model is suitable for Spatio-temporal data mining.
