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SENSITIVITY ANALYSIS OF GENERALIZED FINITE AUTOMATA FOR IMAGE RETRIEVAL

机译:图像检索广义有限自动机的灵敏度分析

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Finite automata have been used mainly for image and video compression in the field of image processing. This paper evaluates finite automata within the context of content based image retrieval in the compressed domain, where an automata-based representation is proposed as a way to avoid image decompression prior to retrieval. The removal of the decompression process aims to improve image matching and retrieval performance with respect to accuracy, speed and computational overheads. The paper presents a sensitivity analysis of image presentation in the automata domain. This study examines the effect of some image alterations on the corresponding automata. Experimental results show that automata yield successful image matching despite image alteration. This reinforces the case for automata-based image representation in content-based retrieval.
机译:有限自动机主要用于图像处理领域中的图像和视频压缩。本文评估了在压缩域中基于内容的图像检索范围内的有限自动机,其中提出了一种基于自动机的表示方法,以避免在检索之前进行图像解压缩。取消减压过程的目的是在准确性,速度和计算开销方面提高图像匹配和检索性能。本文介绍了自动域中图像呈现的敏感性分析。这项研究检查了某些图像更改对相应自动机的影响。实验结果表明,即使图像发生变化,自动机仍能成功完成图像匹配。这加强了在基于内容的检索中基于自动机的图像表示的情况。

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