【摘要】 基于单特征的图像检索系统一般性能较低.提出了一种基于多特征融合的图像检索方法.通过对HSV颜色空间的非等间隔量化,提取一维颜色特征向量及其累加直方图.基于灰度共生矩阵(GLCM)进行纹理特征的提取.将两类特征结合,设计了一种基于多特征融合的图像检索方法.利用相似性度量方法分别对颜色特征和纹理特征以及融合后的特征进行了图像检索实验.结果表明,基于颜色和纹理特征相融合的多特征融合方法具有更好的图像检索性能.更多还原

【Abstract】 Single-feature-based image retrieval system has a lower performance.In this paper,multi-feature fusion based image retrieval is proposed.Through the non-interval quantization of HSV color space,extracts one-dimensional color feature vector and its cumulative histogram.Based on gray level co-occurrence matrix(GLCM) extracted the texture feature.Combination of two types of characteristics is done;an image retrieval based on multi-feature fusion is designed.This paper uses the method of similarity measurement for test of the color features and the texture features,as well as the multi-features.Experiment results show that multi-feature fusion method based on the color and texture features has a better performance.更多还原