摘要
纹理是图像的一个显著特征,也是基于内容检索的一条主要线索。提出了一种基于纹理灰度变化统计的图像检索方法,在水平、垂直、45°和135°方向上统计像素灰度值的变化量,提取关于图像纹理粗细、走向等信息。并将此方法与灰度共生矩阵法和纹理谱法进行比较,从查准率、平均序号和检索时间三方面进行分析,验证了此方法的有效性。同时,还结合颜色特征进行综合检索,并将相关反馈技术融合到算法中,通过多次检索自动调整各特征量的权值以满足用户的检索需求。
Texture is a distinct character of an image,which is an important feature in many CBIR systems.In this paper a new method based on texture features is proposed,which statistic the gray-level variation between neighboring pixels at the directions of horizontal,vertical,45 degree and 135 degree.A prototype system is developed to compare this method, with gray level co-occurrence matrix and texture spectrum in the retrieval accuracies,the rank and the execution time.Experiment results show that the proposed approach is effective.Meanwhile,a method combining both color and texture is proposed,and the technique of relevance feedback is used in the algorithm to enhance the effectiveness and accuracy by adjusting the feature parameters.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第16期83-86,共4页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60472099)
关键词
图像检索
纹理特征
灰度变化统计
相关反馈
image retrieval
texture features
gray variation statistic
relevance feedback
