Local and global features based image retrieval system using orthogonal radial moments
Local and global features based image retrieval system using orthogonal radial moments
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DOI：
10.1016/j.optlaseng.2011.11.012
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发表时间：
2012-05
影响因子：
4.6
通讯作者：
C. Singh;Pooja
中科院分区：
文献类型：
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作者：
C. Singh;Pooja
正交径向矩如Zernike矩、伪Zernike矩和正交傅立叶-梅林矩在文献中已被广泛研究。在传统的矩计算方法中，整个图像强度函数被投影到正交矩多项式上以计算全局特征。在本文中，我们提供了一种新的方法来计算这些时刻，制定有效的本地描述符。计算边缘图像的矩函数以确定图像中的局部变化，其提供图像的局部方面。因此，所获得的局部和全局矩特征相结合，以评估其性能的图像检索系统。矩ZMs，PZMs，和OFFERS，比较在他们的图像检索效果。在各种数据库上进行实验，以检查系统在不同情况下的性能，如受噪声，部分遮挡，失真，复杂结构等影响的图像。实验结果表明，该系统优于现有的最近的方法矩计算图像检索。
Orthogonal radial moments such as Zernike moments, pseudo Zernike moments, and orthogonal Fourier Mellin moments have been studied extensively in the literature. In conventional methods of moment computation, the entire image intensity function is projected upon orthogonal moment polynomials to compute the global features. In this paper, we provide a novel methodology for the computation of these moments, which formulate them as effective local descriptors. The moment functions of edge images are computed to determine the local change in images, which provide the local aspects of the image. Thus, the obtained local and global moment features are combined to evaluate their performance on the image retrieval system. The moments ZMs, PZMs, and OFMMs, are compared in terms of their image retrieval effectiveness. The experiments are performed on various databases to examine the performance of the system in diverse circumstances such as images affected with noise, partial occlusion, distortion, complex structure, etc. The experiments results reveal that the proposed system outperforms the existing recent approaches to moments computation for image retrieval.