利用颜色、纹理和形状特征增强图像检索

A. Ganar, C. Gode, S. Jambhulkar
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引用次数: 30

摘要

基于内容的图像检索技术是通过颜色、形状和纹理三种基本方法来实现的。本文给出了使用这些原语特征检索所需图像的具体路径。我们获得所需图像的技术是CBIR。在CBIR中,首先对HSV颜色空间进行量化,得到颜色直方图和纹理特征;使用这些组件形成一个特征矩阵。然后将该矩阵映射为具有全局颜色直方图和局部颜色直方图的特征,并对其进行分析比较。对于本地图像与数据库中的图像之间的协同矩阵进行检索。对于形状特征的提取,本文采用梯度法。基于这一原理,CBIR系统利用颜色、纹理和形状融合的特征从大型数据库中检索所需的图像,从而比单一特征检索系统在图像检索方面提供了更高的效率或增强,意味着更好的图像检索结果。
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Enhancement of Image Retrieval by Using Colour, Texture and Shape Features
Content based image retrieval technique is done by three primitive methods namely through colour, shape and texture. This paper provides specified path to use these primitive features to retrieve the desired image. The technique by which we obtain the required image is CBIR. In CBIR first the HSV colour space is quantified to obtain the colour histogram and texture features. Using these components a feature matrix is formed. Then this matrix is mapped with the characteristic of global colour histogram and local colour histogram, which are analysed and compared. For the cooccurrence matrix between the local image and the images in the database to retrieve the image. For extracting shape feature gradient method is used here. Based on this principle, CBIR system uses colour, texture and shape fused features to retrieve desired image from the large database and hence provides more efficiency or enhancement in image retrieval than the single feature retrieval system which means better image retrieval results.
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