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Evolutionary Computation Based Optimization of Image Zernike Moments Shape Feature Vector

机译:基于进化计算的图像Zernike矩形状特征向量优化

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摘要

The image shape feature can be described by the image Zernike moments. In this paper, we points out the problem that the high dimension image Zernike moments shape feature vector can describe more detail of the original image but has too many elementsmaking trouble for the next image analysis phases. Then the low dimension image Zernike moments shape feature vector should be improved and optimized to describe more detail of the original image. So the optimization algorithm based on evolutionary computation is designed and implemented in this paper to solve this problem. The experimental results demonstrate the feasibility of the optimization algorithm.
机译:图像形状特征可以通过图像Zernike矩来描述。在本文中,我们指出了一个问题,即高维图像Zernike矩形状特征向量可以描述原始图像的更多细节,但是元素过多,给下一个图像分析阶段带来了麻烦。然后应改进和优化低维图像Zernike矩形状特征向量,以描述原始图像的更多细节。为此,本文设计并实现了基于进化计算的优化算法。实验结果证明了该算法的可行性。

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