首页> 外文会议>International Symposium on Neural Networks(ISNN 2005) pt.1; 20050530-0601; Chongqing(CN) >Affine Invariant Descriptors for Color Images Based on Independent Component Analysis
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Affine Invariant Descriptors for Color Images Based on Independent Component Analysis

机译:基于独立分量分析的彩色图像仿射不变描述子

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In this paper we introduce a scheme to obtain affine invariant descriptors for color images using Independent Component Analysis (ICA), which is a further application of using ICA on contour-known objects. First, some feature points can be found by hue-histogram of the color images in HIS space. Then ICA is applied to extract an invariant descriptor between these corresponding points, which can be a representation of shape similarity between original image and its affine image. This proposed algorithm can also estimate affine motion parameters. Simulation results show that ICA method has better performance compared with Fourier methods.
机译:在本文中,我们介绍了一种使用独立分量分析(ICA)获取彩色图像仿射不变描述子的方案,这是在轮廓已知的物体上使用ICA的进一步应用。首先,可以通过HIS空间中彩色图像的色相直方图找到一些特征点。然后应用ICA提取这些对应点之间的不变描述符,这可以表示原始图像与其仿射图像之间的形状相似性。该提出的算法还可以估计仿射运动参数。仿真结果表明,与傅立叶方法相比,ICA方法具有更好的性能。

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