| 摘要: |
| 针对工件识别问题，提出了一种应用支持向量机（Support Vector Machine，SVM）与组合矩对工件进行识别的方法；通过对提取图像的Hu不变矩进行处理，形成利用组合矩进行工件识别的新方法；改进后的算法降低了特征维数，缩减了识别时间，提高了识别准确率；结合试验比较了两种方法的分类效果，其中提取Hu不变矩作为特征的识别率为82.3%，而采用组合矩作为特征的识别率高达94.1%，高于Hu不变矩作为特征的识别率. |
| 关键词: SVM Hu不变矩 组合矩 工件分类 |
| DOI： |
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| Research on the Application of SVM and Combined Moment in Mechanical Parts Recognition |
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ZHOU Wei-feng，JIANG Juan juan，LIN Yuan sheng，XU Gang
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| Abstract: |
| To solve the problem of mechanical parts recognition in the factory, a method of applying Support Vector Machine and combined moment to recognize mechanical parts is proposed. By extracting the Hu invariant moment of the image, combining the first and second moments into φ12, combining the third and fourth moments into φ34, combining the fifth and sixth moments into φ56, and ignoring the seventh momentφ7, the new method is constructed. The improved algorithm reduces feature dimension and recognition time, and at the same time improves recognition accuracy. The experiment comparing classification effect of the two methods shows that the recognition rate of the method extracting Hu invariant moments as features is 82.3%, while the recognition rate based on the combined moment as features is 94.1% which is higher than the former. |
| Key words: SVM Hu invariant moments combined moment artifacts taxonomy |
