摘要
为有效提取和描述图像特征,提高图像检索性能,提出一种基于纹理、颜色和形状多特征融合的图像检索算法。检测彩色图像的边缘,对其进行变换得到基元图像。遍历基元图像得到基元共生矩阵,对每个基元求梯度值得到基元梯度直方图。将彩色图像量化到64色颜色空间,得到对应的颜色直方图。利用上述3个特征量描述图像特征,并用于图像检索。实验结果表明,与BCTF和MCM算法相比,该算法的查全率和查准率较高,计算复杂度较低。
In order to effectively extract and describe the image feature and improve image retrieval performance,this paper presents a novel image retrieval algorithm based on fusion of texture,color and shape features.The color image edge is detected,and by means of edge image transform,a motif transformed image is obtained.A Motif Co-occurrence Matrix（MCM） is obtained through traversal of the motif transformed image,and the algorithm calculates the gradient of the all motifs of the motif transformed image to get the motif gradient histogram.It obtains the color histogram by uniformly quantize the RGB color image into 64 colors.The image characteristic is described by three image features and it is used to image retrieval.Experimental results indicate that the algorithm has higher precision and recall rate compared with BCTF and MCM algorithm.It can reduce computational complexity.
出处
《计算机工程》
CAS
CSCD
2012年第24期216-219,224,共5页
Computer Engineering
基金
国家自然科学基金资助项目(61165011)
湖南省科技计划基金资助项目(2011GK3172)
关键词
图像检索
多特征融合
基元图像
基元共生矩阵
基元梯度直方图
颜色直方图
image retrieval
multi-feature fusion
motif image
Motif Co-occurrence Matrix（MCM）
Motif Gradient Histogram（MGH）
color histogram
