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A new algorithm of image retrieval based on multiple-feature and FSIM

机译:基于多特征和FSIM的图像检索新算法

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In order to reduce the computation cost of extracting feature, a new algorithm for image retrieval is proposed. This method utilize multiple-feature including ellipse measuring as shape feature, phase congruent and gradient magnitude as the contrast feature for image retrieval in this paper. It not only can fill up a deficiency of the contrast invariant of phase congruent, but also can fully utilize scale and rotation invariance of ellipse measuring. To evaluate the effectiveness of the proposed method, we carried out a series of experiments on shape216 and three color image databases. The experiments show that the proposed method in this paper is more efficient than conventional algorithms.
机译:为了降低特征提取的计算成本,提出了一种新的图像检索算法。该方法利用椭圆测量作为形状特征,相位一致和梯度幅度作为对比度特征的多重特征进行图像检索。它不仅可以弥补全相位对比度不变性的不足,而且可以充分利用椭圆测量的尺度和旋转不变性。为了评估该方法的有效性,我们在shape216和三个彩色图像数据库上进行了一系列实验。实验表明,本文提出的方法比常规算法更有效。

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