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A review on content-based image retrieval system: present trends and future challenges

机译:基于内容的图像检索系统综述:当前趋势与未来挑战

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摘要

The issues of getting similar images with better accuracy is now a challenge in content-based image retrieval (CBIR) system due to exponential rising volume of image databases. In CBIR, first of all image features are extracted. Importance of each low level feature is graded by their repute based on citations in various comparable studies. With this, different weight assignment methods for features like individual weightage, equal assignment of weights and other assignment methods employed in the CBIR systems have been reported. However, the weight assignment to the features of the image is calibrated manually based on its importance in doing accurate searches on particular databases. This paper presents a review on CBIR systems and frequently used features with different weight assignment methods. The future challenge identified from this study is, to make the CBIR system automated for assigning weights to image features. Solutions for reported challenge are also suggested.
机译:由于图像数据库的指数上升量,基于内容的图像检索(CBIR)系统的基于内容的图像检索(CBIR)系统,获得类似图像的问题。 在CBIR中,提取所有图像特征的首先。 每个低级功能的重要性因其基于各种可比研究中的引文而辩护。 为此,已经报道了不同重量分配方法,其具有单独的重量,同等分配的权重和CBIR系统中采用的其他分配方法。 然而,根据其在对特定数据库的准确搜索方面的重要性,手动分配对图像的特征进行手动校准。 本文介绍了CBIR系统的综述,常用的功能具有不同的权重分配方法。 本研究中确定的未来挑战是使CBIR系统自动为图像特征分配权重。 还提出了报告挑战的解决方案。

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