摘要
针对目前彩色纹理图像检索系统结构复杂且时间成本较高的问题,提出一种融合图像颜色与纹理特征的彩色纹理图像检索方法。首先,在HSV空间中分别量化H、S、V三个通道的数据并提取组合直方图的颜色特征。然后,提取V通道数据子带系数的幅值与相位两种分布参数特征作为全局纹理特征;同时,使用局部邻域差分模式(Local Neighborhood Dif⁃ference Pattern)算子提取V通道数据的局部纹理特征,并将所得到的颜色特征、全局纹理特征和局部纹理特征进行有机融合。最后,通过合适的相似性测度完成彩色纹理图像的检索。在VisTex和STex两个流行的彩色纹理图像数据库上进行的检索实验表明,由论文方法所得到的平均检索率较目前典型方法的最优结果分别高出0.96%和0.78%,且检索时间成本更低。因此,论文所提出的彩色纹理图像检索方法是有效的和可行的。
To solve the problem of complex structure and high time cost in current color texture image retrieval system,a color texture image retrieval method based on the fusion of the color and texture features is proposed.First of all,the data of H,S and V channels are quantized in HSV space and the color features of the combined histogram are extracted.Then,the magnitude and phase distribution parameter features of the subband coefficients of V-channel data are extracted as global texture features.At the same time,the local texture features of V-channel data are extracted by local neighborhood difference pattern operator,and the col⁃or features,global texture features and local texture features are organically integrated.Finally,the color texture image retrieval is completed by the appropriate similarity measurement.The retrieval experiments on two popular color texture image databases,name⁃ly VisTex and STex,show that the average retrieval rates obtained by our method are 0.96%and 0.78%higher than that of the cur⁃rent typical methods,respectively,and the retrieval time cost is lower.Therefore,the color texture image retrieval method proposed in this paper is effective and feasible.
作者
徐佳
曲怀敬
张志升
王纪委
魏亚南
张汉元
XU Jia;QU Huaijing;ZHANG Zhisheng;WANG Jiwei;WEI Ya'nan;ZHANG Hanyuan(School of Information&Electric Engineering,Shandong Jianzhu University,Ji'nan 250101)
出处
《计算机与数字工程》
2021年第11期2342-2347,共6页
Computer & Digital Engineering
基金
国家自然科学基金项目(编号:62003191)
山东省自然科学基金项目(编号:ZR2014FM016)
山东省重大科技创新工程(编号:2019JZZY010120)资助。
关键词
彩色纹理图像检索
HSV颜色空间
局部邻域差分模式
纹理特征
相似性测度
color texture image retrieval
HSV color space
local neighborhood difference pattern
texture features
similari⁃ty measurement