摘要
提出了一种基于熵及不变矩特征的图像检索算法。图像首先被划分为不同分块,结合图像信息熵的概念,提出采用单元熵来描述分块特征,从而将图像转化为由单元熵构成的熵矩阵;在此基础上,利用不变矩来描述该熵矩阵的特征,并在对该特征归一化的基础上用于图像检索。结合不变矩的特性,试验中对算法的尺度不变性、旋转不变性、平移不变性及对噪声的不敏感性进行了验证,试验结果证明了算法的有效性。同时,由于熵的对称特性,算法对于图像灰度的变化也有较强的鲁棒性。
A new image retrieval algorithm based on entropy and invariant moments was presented. Though entropy was widely used in image retrieval, it didn＇t contain any spatial information. To solve such problem, an image was firstly partitioned into equal-sized sub-images. Then, unit entropy was introduced to describe its spatial feature based on the definition of entropy. Combined with unit entropy, an image was transformed to an entropy matrix. Then, Hu invariant moments and five new generalization invariant moments of the entropy matrix were calculated and normalized as an index. It is shown through the experiments that this algorithm is scale, rotation and translation invariant. In addition, the algorithm is not sensitive to image noise and the change of the image gray.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2007年第6期102-106,115,共6页
Opto-Electronic Engineering
基金
苏州大学江苏省计算机信息处理技术重点实验室开放基金
河南省教育厅自然科学基础研究基金(137207)
河南理工大学博士基金(B050901)
河南理工大学骨干教师资助基金
河南省基础与前沿技术研究计划项目(072300460050)
关键词
图像检索
单元熵
熵矩阵
不变矩
Image retrieval
Unit entropy
Entropy matrix
Invariant moments
