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A FAST FRACTAL CODING IN APPLICATION OF IMAGE RETRIEVAL

机译:快速分形编码在图像检索中的应用

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摘要

Aiming at content-based image retrieval (CBIR) in fractal domain, this paper puts forward a fast fractal encoding method to extract image features, which is based on a novel non-searching and adaptive quadtree division. As a result, it enhances fractal coding speed sharply, only needs 0.0485 seconds on average for a 256 × 256 image and is approximately 70 times faster than algorithm in addition to good reconstructed image quality. Furthermore, this paper improves image matching algorithm, consequently enhancing the accuracy of query results. In addition, we present a method to further accelerate image retrieval based on the analysis to fractal codes distance and number. Experimental results show that our proposed method is performs highly in retrieval speed and feasible in retrieval accuracy.
机译:针对分形域中基于内容的图像检索(CBIR),提出了一种基于新颖的非搜索自适应四叉树分割的快速分形编码方法来提取图像特征。结果,它显着提高了分形编码速度,对于256×256图像,平均平均仅需要0.0485秒,并且除了具有良好的重建图像质量外,它比算法快大约70倍。此外,本文改进了图像匹配算法,从而提高了查询结果的准确性。另外,基于分形码距离和数量的分析,我们提出了一种进一步加速图像检索的方法。实验结果表明,该方法检索速度快,检索精度可行。

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