摘要
从商空间粒度理论角度分析了图像检索的过程,给出了基于商空间的多粒度图像检索方法。首先根据等价关系R(即图像主色的连通性)将图像划分为不同的区域,然后分别从颜色、形状、空间分布等不同的粒度提取区域的特征属性,利用商空间多粒度属性函数合成思想,将每个粒度下的属性函数合成,形成图像的特征向量,再根据此特征向量计算图像之间的相似度进行检索。实验结果表明,多粒度属性函数合成的检索方法要明显优于单一属性函数下的检索方法;与MTH方法和颜色体积直方图方法相比,其能够更加准确和高效地查找出用户所需要内容的图像,明显地提高了检索精度。
Based on the quotient space and granular computing theory,the image retrieval process was analyzed,and then the method of multi-granularity image retrieval based on quotient was proposed.With the proposed method,an ima-ge was divided into different regions based on the equivalent relation R（i.e.,connectivity of image＇s dominant color） and features of different regions in different granularity levels of color,shape,spatial information were extracted respectively,and then the synthetic feature was obtained by composing the attribute functions in different granularity levels based on the theory of composing multi-granularity attribute functions in the quotient space.Finally,the images were retrieved images by the synthetic feature.Experimental results indicate that the proposed methodin is superior to the method based on single attribute,MTH and the color volume histogram method.
出处
《计算机科学》
CSCD
北大核心
2013年第1期298-301,310,共5页
Computer Science
基金
国家自然科学基金项目(61073146
61272060)
重庆市教委科学技术研究项目(KJ110512)
重庆市自然科学基金项目(cstc2012jjA40047)资助
关键词
商空间
属性函数合成
粒计算
图像检索
Quotient space
Composite attribute function
Granular computing
Image retrieval
