| 引用本文: | 郭欣,王润生.基于多特征的图象目标识别分类.[J].国防科技大学学报,1996,18(3):73-77.[点击复制] |
| Guo Xin,Wang Runsheng.Image Recognition and Classification Based on Multi-feature[J].Journal of National University of Defense Technology,1996,18(3):73-77[点击复制] |
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| 基于多特征的图象目标识别分类 |
| 郭欣, 王润生 |
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(国防科技大学 图书馆 湖南 长沙 410073)
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| 摘要: |
| 文中研究将多特征信息融合技术用于图象目标识别分类的方法，利用图象灰度表面的分形特征与图象的熵特征(非分形特征)所提供的信息进行融合处理，在决策层中运用Dempster-Shafer 证据推理理论，并使用决策规则对目标进行分类。在实验中，将经过信息融合分类的结果与单特征独自分类的结果进行比较。结果表明，多特征信息融合的目标识别方法具有良好的稳定性.准确性和可靠性，能够有效地提高图象分类识别系统的粘确度与容错性。 |
| 关键词: 特征提取，目标识别与分类，Dempster-Shafer 证据推理 |
| DOI： |
| 投稿日期：1996-03-12 |
| 基金项目: |
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| Image Recognition and Classification Based on Multi-feature |
| Guo Xin, Wang Runsheng |
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(Library of NUDT, Changsha，410073)
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| Abstract: |
| Multi-feature fusion technique is used to recognize and classify the image target in this paper. We extract the fractal feature and gray entropy from the image，then use Dempster-Shafer's Evidential Reasoning to fuse the information at the report level. Some decision strategies are used to recognize and classify the image. In experiment，we compare the results obtained from Multi-feature fusion with those obtained from single feature. The final results indicate that the Multi-feature fusion method is stable，reliable，and can efficiently improve the accuracy and the ability of fault tolerance. |
| Keywords: feature extract,target recognition and c1assification,Dempster Shafer's Evidential Reasoning |
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