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A Novel Image Retrieval Method Based on Mutual Information Descriptors

机译:一种基于互信息描述符的新型图像检索方法

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In this paper, we propose a novel image retrieval method based on mutual information descriptors (MIDs). Under the physiological property of human eyes and human visual perception theory, MIDs are extracted to encode the internal correlation relationship among multiple image feature spaces, characterizing image contents with mutual information features based on the low-level image features, such as color, shape etc., then, the mutual information features fusion strategy is used to imitate the information transfer process in nervous system. When using the MIDs proposed to image retrieval, we can get many advantages such as low dimensionality, a certain robustness of geometric distortions and noise, and describing the human visual retrieval mechanism effectively. Experimental results show that MIDs have high indexing and retrieving performance compared with existing methods for content-based image retrieval (CBIR).
机译:在本文中,我们提出了一种基于互信息描述符(中段)的新型图像检索方法。在人眼和人类视觉感知理论的生理性质下,提取中期以对多个图像特征空间之间的内部相关关系进行编码,其特征在于基于低级图像特征的相互信息特征,例如颜色,形状等。然后,互信息特征融合策略用于模仿神经系统中的信息传输过程。当使用所提出的MID患者进行图像检索时,我们可以获得许多优点,如低维度,几何扭曲和噪声的一定稳健性,并有效地描述人类视觉检索机制。实验结果表明,与基于内容的图像检索(CBIR)的现有方法相比,中期具有高分性和检索性能。

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