采用改进的小波和颜色矩的色纺面料图像检索

Image retrieval of colored spun fabrics using modified wavelet transform method and color moments

传统的色纺面料检索方法效率低下、精度低,针对色纺面料颜色种类丰富、纹理复杂多变的特点,文章提出一种基于颜色矩和改进的小波变换结合的图像检索算法。采集色纺面料图像并建立标准图像数据库;分别采用颜色矩和改进的小波变换的方法提取色纺面料图像的颜色特征和纹理特征,使用欧氏距离测度的方法计算两种特征的子相似度;采用加权求和的方式获得图像的总体相似度,排序得到检索结果。试验中分别讨论了不同特征权重对检索结果的影响,验证了当颜色特征权重占0.8纹理特征权重占0.2时,检索结果最优。对比试验表明,该算法可兼顾颜色特征和纹理特征对检索结果的影响,平均检索精度mAP达到80.8%,优于现有方法。

In view that traditional retrieval methods of colored spun fabrics are inefficient and inaccurate,while colored spun fabrics are characterized by rich colors and complex textures,an image retrieval algorithm combining color moment and modified wavelet transform was proposed.Firstly,colored spun fabric images were collected to establish a standard image database.Secondly,the color features and texture features of the colored spun fabric images were extracted using color moments and modified wavelet transform method respectively.The sub-similarity of color features and texture features were measured using Euclidean distance measurement method.Finally,the overall similarity of the images was obtained through weighted summation and the retrieval results were obtained by sorting.In the experiment,the influence of different feature weights on the retrieval results was discussed,and it was verified that when the color feature weights accounted for 0.8 and texture feature for 0.2 respectively,the retrieval result was optimal.The results of contrast experiment have shown that the algorithm can take into account the effects of color features and texture features on retrieval results,with an average retrieval precision ratio of 80.8%which is superior to the existing method.