检索结果-内蒙古大学图书馆

An adaptive and fast valley emphasis multilevel otsu thresholding algorithm

An adaptive and fast valley emphasis multilevel otsu thresho...

2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013

作者： Long, Jianwu Shen, Xuanjing Chen, Haipeng Zhang, He College of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun Jilin China

ISBN: (纸本)1601322534

The multilevel thresholding problem is a challenge task due to the fact that the computation is usually very time-consuming for obtaining the optimal multilevel thresholds. Though the state-of-the-art multilevel thresholding algorithms applied various meta-heuristic techniques or acceleration strategies, they still directly searched the optimal thresholds in the whole histogram only for the fixed thresholds number given by the user. Considering that the optimal thresholds usually locate at the valleys of the histogram, we propose an adaptive and fast valley emphasis multilevel Otsu thresholding algorithm (AFVEO). We constrain the searching space in locations of all valleys of the histogram, and it can greatly reduce the iterations required for computing the between-class variance due to the fact that the number of valleys is much fewer than the size of the histogram. And most important we can obtain the optimal multilevel thresholds for different thresholds number without fixed one given by the user. The experimental results indicate that the proposed method is more efficient than traditional Otsu method, recursive Otsu method, valley emphasis Otsu method and neighborhood valley emphasis Otsu method. © 2013 CSREA Press. All rights reserved.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Visual saliency and extended hidden markov model based approach for image splicing detection

Visual saliency and extended hidden markov model based appro...

引用

2013 International Conference on Mechanical and Electronics engineering, ICMEE 2013

作者： Li, Xiang Shen, Xuan Jing Lv, Ying Da Chen, Hai Peng College of Computer Science and Technology Jilin University Changchun Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China

ISBN: (纸本)9783037858103

In order to improve the detection accuracy of spliced images, a new blind detection based on visual saliency was proposed in this paper. Firstly, create the edge conspicuous map by an improved OSF-based method, and extract fixations by visual attention model. Then locate those fixations on conspicuous edges by conspicuous edge positioning method. Accordingly, key feature fragments can be captured. Secondly, extract Extended Hidden Markov Model features, and reduce their dimension by SVM-RFE. Finally, support vector machine was exploited to classify the authentic and spliced images. The experimental results showed that, when testing on the Columbia image splicing detection dataset, the detection accuracy of the proposed method was 96.68%. © (2013) Trans Tech Publications, Switzerland.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

The morphological component analysis and its application to color-gray image fusion

引用

Journal of computational Information Systems 2013年第24期9卷 9849-9856页

作者： Zhang, Xiaoli Feng, Yuncong Li, Xiongfei Wang, Song Key Laboratory of Symbolic Computation and Knowledge Engineering for Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Jilin University Changchun 130012 China Jilin Petrochemical Company PetroChina Co. Ltd. Changchun 132022 China

This paper focuses on a new color-gray image fusion algorithm based on Morphological Component Analysis (MCA) which is a novel decomposition (separation) method based on sparse representation of signals and images. The interest of the newly proposed fusion algorithm is the ability of preserving textural information. In our fusion scheme, color original images are transformed into gray-scale images firstly. Secondly, we discompose the gray-scale images into smooth parts and textural parts, and thirdly fuse them respectively;fourthly, gray-scale fused image is obtained by adding the two fused parts. Finally, the color fused images are achieved based on the gray-scale fused image. We tested the algorithm in medical and biological images, and experimental results justify the superiority of the fusion algorithm. Copyright © 2013 Binary Information Press.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Solving the optimal power flow problem via a non-interior path following algorithm

引用

Journal of computational Information Systems 2013年第3期9卷 1191-1198页

作者： Su, Menglong Liu, Le Wang, Jian Cai, Hua Mathematics and Information Science College Luoyang Normal University Luoyang 471022 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China College of Mathematics and Information Science Ocean University of China Qingdao 266000 China College of Mathematics Jilin University Changchun 130012 China

In this paper, we propose a non-interior path following algorithm for solving the optimal power flow problem. By using the new approach, we can choose initial guesses arbitrarily in the whole space of n dimensional Euclidean space. This can improve the computational efficiency of the algorithm greatly than before. Some numerical examples are presented to illustrate the results of this paper. Copyright © 2013 Binary Information Press.

关键词： computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Image resizing by color energy updating

引用

Guangxue Jingmi Gongcheng/Optics and Precision engineering 2013年第SUPPL期21卷 264-270页

作者： Zhao, Hong-Wei Wang, Zhen Liu, Ping-Ping Li, Qing-Liang School of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China

A new image resizing algorithm was proposed based on a color space and an energy updating mechanism. First, the concept of color space was introduced into image resizing algorithm and the pixel's energy function was re-built based on the gradient of gray space and color space. Three kinds of color energy functions were tested and the energy function in HSI space was finally chosen because of its excellent performance. Additionally, since image resizing might badly corrupt the contours of main areas in an original image and might further affect the understanding of the image, an energy updating mechanism was proposed. The energy updating mechanism could increase the neighborhood energy values where a pixel had been deleted. By doing so, it could decrease the probability that seams cross this area again, thus the contour of this area could be protected well. In experiments, the degree of Scale Invariant Feature Transform (SIFT) matching between original image and resized image with different λ values was calculated. The best performance shows that the proportion between the color and gray energy functions was 7:3. By comparing the proposed method with other two state of arts algorithms, it indicates that the shape of main area will be better preserved with the proposed algorithm without introducing any more complexity.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Improved filter feature selection methods by samples localization

引用

Journal of Bionanoscience 2013年第4期7卷 371-377页

作者： Sun, Ying Wang, Yan Chen, Liang Du, Wei Cao, Zhongbo Zhou, You College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China College of Chemistry Jilin University Changchun 130012 China

With the development of high-throughput microarray technology, a large number of microarray data has been obtained by tens of thousands of simulation experiments on gene expression. However, due to the high cost, gene expression data of each experiment has a small number of samples for tens of thousands of genes. Furthermore, most of the genes, such as the features, are unrelated to classification. Therefore, developing an effective and robust method to extract informative genes subset from high dimensional microarray data is a challenging and important issue for microarray data analysis. In this article, we propose an improved feature selection method by samples localization. We only use localized samples to select genes subset, in order to effectively overcome the influence on the results of feature selection by outlier samples and the distribution of samples. Experimental results obtained by SVM classifiers on Leukemia dataset, Prostate dataset, Colon dataset, Breast dataset, DLBCL dataset and Lung dataset demonstrate that the proposed method is superior to those original filter feature selection methods both in best and average accuracies. Copyright © 2013 American Scientific Publishers. Website © 2013 Publishing Technology.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Some new signature schemes and secret sharing schemes based on the Gröbner basis cryptosystems

引用

Journal of computational Information Systems 2013年第13期9卷 5133-5140页

作者： Li, Hengyan Chang, Shuizhen Xu, Zhonghai Mathematics and Information Science College North China University of Water Resources and Electric Power Zhengzhou 450011 China Mathematics and Information Science College Luoyang Normal University Luoyang 471022 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of Technology Harbin 150080 China

In this paper, we introduce some new signature schemes and secret sharing schemes from the known Gröbner basis cryptosystems. Then, we discuss the issues related to the security of these schemes. Finally, we draw... 详细信息

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

A New Mobile Visual Search System Based on the Human Visual System

A New Mobile Visual Search System Based on the Human Visual ...

引用

第四届国际仿生工程学术会议

作者： Bo Zhao Hongwei Zhao Pingping Liu Guihe Qin School of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education

We describe a novel mobile visual search system based on the saliency mechanism and sparse coding principle of the human visual system (HVS). In the feature extraction step, we first divide an image into different regions using the saliency extraction algorithm. Then scale-invariant feature transform (SIFT) descriptors in all regions are extracted while regional identities are preserved based on their various saliency levels. According to the sparse coding principle in the HVS, we adopt a local neighbor preserving Hash function to establish the binary sparse expression of the SIFT features. In the searching step,

关键词： mobile vision search, human vision system, saliency, sparse coding, Hash, SIFT descriptor.

来源：评论

学校读者我要写书评

暂无评论

Making Simple Tabular Reduction works on negative table constraints

Making Simple Tabular Reduction works on negative table cons...

引用

27th AAAI Conference on Artificial Intelligence, AAAI 2013

作者： Li, Hongbo Liang, Yanchun Guo, Jinsong Li, Zhanshan Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)9781577356158

Simple Tabular Reduction algorithms (STR) work well to establish Generalized Arc Consistency (GAC) on positive table constraints. However, the existing STR algorithms are useless for negative table constraints. In this work, we propose a novel STR algorithm and its improvement, which work on negative table constraints. Our preliminary experiments are performed on some random instances and a certain benchmark instances. The results show that the new algorithms outperform GAC-valid and the MDD-based GAC algorithm. Copyright © 2013, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

An Ant Colony Optimization Based Dimension Reduction Method for High-Dimensional Datasets

引用

Journal of Bionic engineering 2013年第2期10卷 231-241页

作者： Ying Li Gang Wang Huiling Chen Lian Shi Lei Qin College of Computer Science and Technology Jilin University Changchun 130012 P. R. China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 P. R. China College of Geo Exploration Science and Technology Jilin University Changchun 130026 P. R. China College of physics and electronic information Wenzhou University Wenzhou 325035 P. R. China

In this paper, a bionic optimization algorithm based dimension reduction method named Ant Colony Optimization -Selection （ACO-S） is proposed for high-dimensional datasets. Because microarray datasets comprise tens of thousands of features （genes）, they are usually used to test the dimension reduction techniques. ACO-S consists of two stages in which two well-known ACO algorithms, namely ant system and ant colony system, are utilized to seek for genes, respectively. In the first stage, a modified ant system is used to filter the nonsignificant genes from high-dimensional space, and a number of promising genes are reserved in the next step. In the second stage, an improved ant colony system is applied to gene selection. In order to enhance the search ability of ACOs, we propose a method for calculating priori available heuristic information and design a fuzzy logic controller to dynamically adjust the number of ants in ant colony system. Furthermore, we devise another fuzzy logic controller to tune the parameter （q0） in ant colony system. We evaluate the performance of ACO-S on five microarray datasets, which have dimensions varying from 7129 to 12000. We also compare the performance of ACO-S with the results obtained from four existing well-known bionic optimization algorithms. The comparison results show that ACO-S has a notable ability to＂ generate a gene subset with the smallest size and salient features while yielding high classification accuracy. The comparative results generated by ACO-S adopting different classifiers are also given. The proposed method is shown to be a promising and effective tool for mining high-dimension data and mobile robot navigation.

关键词： gene selection feature selection ant colony optimization high-dimensional data

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：