矩不变量在目标形状识别中的应用研究
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The Research and Application of Moment Invariants in Object Shape Recognition
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    摘要:

    本文提出了图像分割的一种新的算法, 简单实用。实验表明, 它优于经典的最大方差准则门限法和最大熵分割法。本文利用中心矩构成仿射不变量, 作为目标的特征。本文提出了利用上述各特征的一种数据融合算法。实验表明, 利用该算法进行识别时正确率高, 且所用时间短, 效果好。本文所提供的方法在对18类目标138幅图像进行识别时总识别正确率高于85%。

    Abstract:

    This paper first presented a novel and simple method of image segmentation. Experiments illustrates that this method is more effective than some traditional methods, such as maximum-square-error threshold-method and mazimum-entropy threshold-method. In the algorithm of object recognition, we construct object's characters based on four affine monent invariants. Furthermore, we proposed a data-fusion algorithm based on the above characters. The performance of the proposed technique in the recognition experiments of 138 pieces of image, which gained from 18 kinds of objects, is also involved. The experiment result is satisfactory, which the correct-ratio of object recognition is above 85%.

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引用本文

颜孙震,孙即祥,王晓华,等.矩不变量在目标形状识别中的应用研究[J].国防科技大学学报,1998,20(5):75-80.
Yan Sunzhen, Sun Jixiang, Wang Xiaohua, et al. The Research and Application of Moment Invariants in Object Shape Recognition[J]. Journal of National University of Defense Technology,1998,20(5):75-80.

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  • 收稿日期:1998-03-03
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  • 在线发布日期: 2014-01-03
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