基于直觉模糊集的图像相似性度量  

Image Similarity Measure Based on Intuitionistic Fuzzy Set

作　　者：徐少平[1,2] 张华[1] 江顺亮[2] 叶发茂[2] 熊宇虹[2] 

机构地区：[1]南昌大学机电工程学院江西省机器人与焊接自动化重点实验室,南昌330031 [2]南昌大学信息工程学院计算机科学与技术系,南昌330031

出　　处：《模式识别与人工智能》2009年第1期156-161,共6页Pattern Recognition and Artificial Intelligence

基　　金：国家863计划项目(No.2007AA04Z242);国家自然科学基金项目(No.50863003;60863002)资助

摘　　要：提出一种基于HSV颜色直方图的图像直觉模糊模型.在该模型下图像可看作是一个直觉模糊集合(IFS),图像之间的相似程度可通过计算直觉模糊集合之间距离来度量.实验数据表明:在HSV颜色空间下基于直觉模糊集的相似性度量能够有效用于图像数据库的查询,并且比普通基于模糊集的相似性度量和直方图距离在查询正确率方面提高5%～10%.An intuitionistic fuzzy model for images based on the HSV color histogram is proposed. The image can be considered as an intuitionistic fuzzy set （IFS） by this model. Similarity measures are originally introduced to express the comparison between two fuzzy sets, and they can be used to reflect the resemblance of images. Experimental results show that the proposed approach can efficiently process queries of an image database in HSV color space and its accuracy rate is 5% - 10% higher than those of fuzzy similarity measures and conventional histogram distances.

关 键 词：相似性度量 图像直觉模糊模型 HSV颜色直方图 基于内容的图像检索(CBIR) 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]