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基于相似度的双搜索多目标识别算法 被引量:5
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作者 冷何英 王敬儒 蔡敬菊 《红外与激光工程》 EI CSCD 北大核心 2002年第6期465-468,共4页
在分析远距离多目标特性的基础上,提出了一种基于相似度的粗精双搜索多目标识别算法。在粗搜索阶段,首先利用圆形形态学模板在滤波后的二值化图像中快速搜索候选目标,再利用"距离相似度"原则进行候选目标的聚类分析,以同一目... 在分析远距离多目标特性的基础上,提出了一种基于相似度的粗精双搜索多目标识别算法。在粗搜索阶段,首先利用圆形形态学模板在滤波后的二值化图像中快速搜索候选目标,再利用"距离相似度"原则进行候选目标的聚类分析,以同一目标内各候选目标点的形心位置作为局部熵处理区域中心。在精搜索阶段,以最大熵值点为种子点进行目标区域生长。为了减少运算量,提高实时性,还采用基于熵相似度、简单连接法与子区合并法相结合的改进型区域生长法,重构单个目标。仿真结果表明该算法可快速、准确地实现对5个目标的识别。 展开更多
关键词 相似 双搜索 多目标识别算法 距离相似 熵相似度 区域生长
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Similarity measure on intuitionistic fuzzy sets 被引量:5
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作者 PARK Jean-Ho HWANG Jai-Hyuk +2 位作者 PARK Wook-Je 魏荷 LEE Sang-Hyuk 《Journal of Central South University》 SCIE EI CAS 2013年第8期2233-2238,共6页
Study of fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) was proposed and analyzed. Unlike fuzzy set, IFSs contain uncertainty named hesitance, which is contained in fuzzy membership function ... Study of fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) was proposed and analyzed. Unlike fuzzy set, IFSs contain uncertainty named hesitance, which is contained in fuzzy membership function itself. Hence, designing fuzzy entropy is not easy because of many entropy definitions. By considering different fuzzy entropy definitions, fuzzy entropy on IFSs is designed and discussed. Similarity measure was also presented and its usefulness was verified to evaluate degree of similarity. 展开更多
关键词 similarity measure MULTI-DIMENSION discrete data relative degree power interconnected system
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Quantitative comparison of similarity measure and entropy for fuzzy sets
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作者 JUNG Dong-yean CHOI Jung-Wook +1 位作者 PARK Wook-Je LEE Sang-Hyuk 《Journal of Central South University》 SCIE EI CAS 2011年第6期2045-2049,共5页
Comparison and data analysis with the similarity measures and entropy for fuzzy sets were carried out. The distance proportional value between the fuzzy set and the corresponding crisp set was considered by the fuzzy ... Comparison and data analysis with the similarity measures and entropy for fuzzy sets were carried out. The distance proportional value between the fuzzy set and the corresponding crisp set was considered by the fuzzy entropy. The relation between the similarity measure and the entropy for fuzzy set was also analyzed. The fuzzy entropy was reformulated as the dissimilarity measure. Furthermore, crisp set having the minimum uncertainty with respect to the corresponding fuzzy set was also proposed. Finally, derivation of a similarity measure from entropy with the help of total information property was derived. A simple example shows the relation between similarity measure and fuzzy entropy, in which the summation of similarity measure and fuzzy entropy represents a constant value. 展开更多
关键词 similarity measure fuzzy entropy minimum uncertainty quantitative comparison
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