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Video image retrieval on the basis of subregional co-occurrence matrix texture features and normalised correlation

机译:基于子区域共生矩阵纹理特征和归一化相关的视频图像检索

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This paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore, this paper proposes a simple segmentation method, which is to divide an image into high and low entropy regions by using picture information measure (PIM). Also, in order to describe texture characteristics of each region, this paper suggests six different texture features produced on the basis of co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of each texture feature values. Finally, this proposed algorithm is applied to various images and produces competitive results.
机译:本文提出了一种利用子区域纹理特征的简单有效的图像检索算法。为了根据其内容检索图像,需要获得精确的分割。但是,这非常困难并且需要很长的计算时间。因此,本文提出了一种简单的分割方法,即通过使用图像信息度量(PIM)将图像分为高熵区域和低熵区域。另外,为了描述每个区域的纹理特征,本文提出了基于共现矩阵产生的六个不同纹理特征。对于图像检索系统,采用归一化的相关性作为相似度函数,其不依赖于每个纹理特征值的范围。最后,该算法被应用于各种图像并产生竞争结果。

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