基于模糊集的感知分组

Hang-Bong Kangt, E. Walker
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引用次数: 7

摘要

提出了一种基于模糊集的点、线段、椭圆弧段关系检测方法。提取定义关系的适当约束。为每个约束分配合适的模糊隶属函数。然后用模糊集运算组合约束来描述有意义的关系。根据这些有意义的关系,进行感知分组。在共线和共椭圆关系的基础上描述了分组方法。讨论了分组在高级视觉处理中的重要性。采用基于框架的知识表示方案实现了图像数据感知分组的原型系统,并给出了对真实图像数据的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perceptual grouping based on fuzzy sets
The authors propose a new approach based on fuzzy sets for detecting relations among points, line segments, and elliptic arc segments. Appropriate constraints defining the relations are extracted. A suitable fuzzy membership function is assigned to each constraint. Then the constraints are combined by fuzzy set operations to describe meaningful relations. According to these meaningful relations, a perceptual grouping is executed. Grouping methods are described on the basis of collinear and coelliptic relations. A measure of the significance of grouping for high-level vision processing is discussed. A prototype system for perceptual grouping from image data was implemented using a frame-based knowledge representation scheme, and experimental results for real image data are presented.<>
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