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Enhancement of semantics in CBIR

机译:增强CBIR中的语义

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摘要

Although much research has been done in the area of content based image retrieval (CBIR), little progress has been made to fully implement an engine solely based on the search of image content. This paper examines one of the basic problems in pattern recognition which highlights the difficulty in the area of content understanding in CBIR, i.e. the inability of current systems to fully incorporate low level features of image, such as intensity, colour, texture, shape and spatial constraints characteristics, with the high level features such as semantic content. To further the development of content based image processing, semantic algorithms should be combined with low level features and be used to process the image objects.
机译:虽然在基于内容的图像检索(CBIR)的区域中已经完成了多项研究,但是已经仅仅基于图像内容的搜索来完全实现发动机的进展甚微。本文审查了模式识别中的一个基本问题,它突出了CBIR中内容理解领域的难度,即当前系统的无法完全包含图像的低级特征,例如强度,颜色,纹理,形状和空间约束特征,具有高级功能,如语义内容。为了进一步开发基于内容的图像处理,语义算法应与低电平特征组合,并用于处理图像对象。

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