Abstract:The bundle feature based method is effective for near-duplicate image retrieval. However, there are some limitations due to the use of SIFT descriptor and coordinate information. Therefore, in this paper color features are integrated into traditional SIFT representation to form the multi-features bundle and two kinds of robust orders between points in bundle feature are introduced-the circle order and the main orientation order. Firstly, the color distribution features of interesting points are extracted and indexing is embedded into them, and then the potential false matchings are discarded by the Kullback-Leibler divergence of corresponding color features. Secondly, the geometric loss score is computed according to the inconsistency between orders of the distance from points to the center of bundle region or the orders of the angle between the orientation of points and main orientation of bundle. The experiment on Copydays dataset shows the improved retrieval performance by adding color features and better circle order and main orientation order geometric constraints of the bundle feature in the image retrieval task.
宋歌,金鑫,谭晓阳. 基于多特征绑定的近似重复图像检索*[J]. 模式识别与人工智能, 2016, 29(10): 943-950.
SONG Ge, JIN Xin, TAN Xiaoyang. Near-Duplicate Image Retrieval Based on Multi-features Bundle. , 2016, 29(10): 943-950.
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