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Attribute associated image retrieval and similarity reranking

机译:属性相关的图像检索和相似性重新排序

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摘要

Existence of countless digital images has given rise to image retrieval in many applications. Conventional image databases being text-annotated pose two major problems of keywords for images and complexity. Hence, retrieval systems based on image's visual content are more desirable [1]. The content based image retrieval (CBIR) technique, employed here uses visual cues to retrieve images. This technique is query based, extracts the most vital attributes like color, shape and texture. Automatic extraction of spatial based color feature and invariant Fourier descriptors makes it more flexible. The extent of each attribute is obtained from the user, compared with attributes of images in database and most similar images are retrieved based on the degree of similarity.
机译:无数数字图像的存在在许多应用中引起了图像检索。传统的图像数据库是文本注释对图像和复杂性的关键字构成了两个主要问题。因此,基于图像的视觉内容的检索系统更为希望[1]。这里采用的基于内容的图像检索(CBIR)技术使用视觉提示来检索图像。此技术是基于查询的,提取最重要的属性,如颜色,形状和纹理。基于空间的颜色特征和不变的傅里叶描述符的自动提取使其更加灵活。与用户中获得每个属性的程度,与数据库中的图像属性相比,并且基于相似度的程度检索大多数相似的图像。

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