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A CONTEXT-BASED APPROACH FOR COLOR IMAGE RETRIEVAL

机译:基于上下文的彩色图像检索方法

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摘要

In this paper, a color image retrieval method based on the primitives of images will be proposed. First, the context of each pixel in an image will be defined. Then, the contexts in the image are clustered into several classes based on the algorithm of fast noniterative clustering. The mean of the context in the same class is considered as a primitive of the image. The primitives are used as feature vectors. Since the numbers of primitives between images are different, a specially designed similarity measure is then proposed to do color image retrieval. To better adapt to the preferences of users, a relevance feedback algorithm is provided to automatically determine the weight of each primitive according to the user's response.
机译:本文提出了一种基于图像原语的彩色图像检索方法。首先,将定义图像中每个像素的上下文。然后,基于快速非迭代聚类算法,将图像中的上下文聚类为几个类别。同一类中上下文的均值被认为是图像的基元。这些原语用作特征向量。由于图像之间的基元数量不同,因此提出了一种经过特殊设计的相似性度量来进行彩色图像检索。为了更好地适应用户的喜好,提供了一种相关性反馈算法,可以根据用户的响应自动确定每个图元的权重。

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