| 基于全局特征与局部特征的图像分级匹配算法研究及应用 |
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| 引用本文： | 朱奇光,王梓巍,陈颖. 基于全局特征与局部特征的图像分级匹配算法研究及应用[J]. 中国机械工程, 2016, 27(16): 2211 |
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| 作者姓名： | 朱奇光 王梓巍 陈颖 |
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| 作者单位： | 1.燕山大学，秦皇岛，0660042.河北省特种光纤与光纤传感重点实验室，秦皇岛，066004 |
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| 基金项目： | 国家自然科学基金资助项目(61201112)；河北省自然科学基金资助项目(F2016203245)；河北省普通高等学校青年拔尖人才计划资助项目（BJ2014056） |
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| 摘 要： | 移动机器人基于拓扑地图导航时要求图像特征提取与匹配算法具有高的精度和鲁棒性、良好的实时性，针对此，提出了基于全局特征和局部特征的图像分级匹配算法。首先对输入的待匹配图像应用改进的形状上下文算法提取全局特征与图像库中图像进行遍历粗匹配，得到与当前待匹配图像相似度最高的3幅图像并构建临时图像库;然后利用改进的SIFT算法提取输入图像局部特征与临时图像库中3幅图像的局部特征进行精确匹配，最终得到与待匹配图像相似度最高的图像作为匹配结果输出。所提出的图像分级匹配算法将基于全局特征的改进形状上下文算法和基于局部特征的改进SIFT算法相结合，从而达到优势互补的目的。实验结果表明，该算法在机器人基于拓扑地图导航过程中有效地提高了图像匹配效率，缩短了运行时间。
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| 关 键 词： | 移动机器人 图像匹配 改进形状上下文 改进SIFT |
Investigation and Application on Image Hierarchical Matching Algorithm Based on Global Feature and Local Feature |
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| Zhu Qiguang,Wang Ziwei,Chen Ying. Investigation and Application on Image Hierarchical Matching Algorithm Based on Global Feature and Local Feature[J]. China Mechanical Engineering, 2016, 27(16): 2211 |
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| Authors: | Zhu Qiguang Wang Ziwei Chen Ying |
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| Affiliation: | 1.Yanshan University，Qinhuangdao，Hebei,0660042.The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province,Qinhuangdao，Hebei,066004 |
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| Abstract: | Aiming at the problems that the image feature extraction and match algorithm should have high accuracy, good performance in real-time and robustness when the mobile robot navigated based on topological map, the paper proposed a new image hierarchical matching algorithm based on the global feature and local fusion. First, the improved shape context algorithm was applied to the input images to be matched to extract the global features which were matched roughly with the images in the database, obtaining 3 images that had the highest similarity to the current image which constituted a temporary image database. Then, the improved SIFT algorithm were used to extract local feature of the input images which were matched accurately with the local feature of the 3 images in the temporary image database, finally obtaining the image with highest similarity as the match results. The image hierarchical matching algorithm based on the global feature and local feature combined the improved shape context algorithm based on global features and the improved SIFT algorithm based on local features, so as to achieve the purpose of complementary advantages. The experimental results show that this algorithm can effectively improve the matching efficiency and reduce the running time when the mobile robots navigate based on topological map. |
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| Keywords: | mobile robot image matching improved shape context improved SIFT |
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