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Blurred Image Recognition by Legendre Moment Invariants

机译:勒让德矩不变式对图像的模糊识别

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摘要

Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments.
机译:处理模糊图像是许多图像应用程序中的关键问题。获得相对于中心对称模糊不变的模糊不变性的现有方法是基于几何矩或复数矩的。在本文中,我们提出了一种使用正交勒让德矩构造一组模糊不变量的新方法。提出并证明了勒让德矩对模糊图像的一些重要性质。利用各种点扩展函数和不同的图像噪声来评估所提出的描述符的性能。还提供了本方法与先前方法在模式识别准确性方面的比较。实验结果表明,与基于几何或复杂矩的方法相比,所提出的描述符对噪声更鲁棒,并且具有更好的判别能力。

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