Quaternion moment and its invariants for color object classification

Quaternion moment and its invariants for color object classification
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颜色对象分类的四元数矩及其不变量

DOI:
10.1016/j.ins.2014.03.037
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发表时间:
2014-07
影响因子:
8.1
通讯作者:
Ming Zhu
Ming Zhu
中科院分区:
计算机科学1区
文献类型:
--
作者:
Liqiang Guo;Ming Dai;Ming Zhu

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矩不变量是计算机视觉中重要的形状描述符。在这项研究中,我们提出了新的彩色图像四元数矩描述子集。它们是在四元数框架下构造的,是灰度图像的复矩不变量的扩展。在需要相似性不变性的彩色图像处理和彩色目标识别任务中,这是一个有用的工具。所提出的四元数矩不变量的优点在于,它们不仅可以对彩色图像进行整体处理,而且还可以对灰度图像进行处理。此外,该方法的计算复杂度远低于极坐标下定义的四元数Zernike矩。给出了一个将四元数矩不变量作为模式特征用于彩色目标分类应用的例子。理论和实验结果表明,所提出的描述子比其他基于矩的竞争方法具有更好的性能。
Moment invariants are important shape descriptors in computer vision. In this study, we propose new sets of quaternion moment descriptors for color image. They are constructed in the quaternion framework and are an extension of complex moment invariants for grayscale images. This is a useful tool in color image processing and color object recognition tasks that require the similarity invariance. The advantage of the proposed quaternion moment invariants is that they can not only process color image in a holistic manner but also grayscale one. In addition, the computational complexity of the proposed method is much lower than the quaternion Zernike moments defined in the polar coordinates. An example of using the quaternion moment invariants as pattern features for a color object classification application is given. Theoretical and experimental results show that the proposed descriptors perform better than the other competing moment-based methods.
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