检索结果-内蒙古大学图书馆

10th IEEE International Conference on Fuzzy Systems

作者： Zeng, ZG Yan, H Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia

ISBN: (纸本)078037293X

This paper presents an approach to object feature extraction and object matching for line object processing. The invariant features of objects have been extracted based on inertia coordinate systems. Weighted fuzzy dissimilarity is proposed as a matching variable. To simplify the optimal object matching, an optimal matching pair theorem is proposed. Experiments are conducted for verifying the feature extraction and the optimal matching pair theorem.

关键词： object feature object matching fuzzy dissimilarity computer animation technical area pattern recognition and image processing

来源：评论

学校读者我要写书评

暂无评论

CALCULATION OF EXACT STATISTICS ON DIRECTIONAL-DATA IN THE 2-D SPACE

引用

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 1995年第1期E78D卷 37-48页

作者： KAWAKAMI, H Kyoto Inst of Technology Kyoto-shi Japan

This paper describes a new algorithm for calculating exact statistics on directional data and its application to pattern processing. Although information about directional characteristics is practically useful in image processing, e.g. texture analysis or color segmentation, dominant information is not always extracted as exact statistics on directional data. The main reason is concerned with periodicity inherent in directional data. For example, an expectation of a random variable X is defined as integral xp (x) dx, where p(x) is a probability density function of X;therefore, when a random direction D is distributed only at - 170[degrees] and 170[degrees] with same probability density, the expectation of D leads to 0[degrees] if nothing about the periodicity is considered. We would, however, expect that the exact expectation of D should be +/- 180[degrees]. To overcome the problem, we, at first, define a directional distance in such a form that can introduce the periodicity. Then, we propose an idea of defining directional statistics by a problem of minimizing an arithmetic mean of squared directional distances to each sample direction. Because the periodicity is introduced to the directional distance definition, the directional statistics are calculated as the exact statistics on directional data. Although the introduced periodicity might cause the minimization to be complex, we can compensate the complexity by introducing recurrence formulas;consequently, dominant information can efficiently be extracted as the directional statistics from those data. Experiments on their applications to pattern processing show that the proposed algorithm works well in detecting (1) divergent points of distorted vector field patterns with noise and (2) moving directions from translational movement vector fields.

关键词： pattern recognition and image processing

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：