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A Document Image Retrieval Method Based on Multi-feature Fusion

机译:基于多特征融合的文档图像检索方法

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With the rising popularity of mobile devices, recent years have witnessed a growing interest in document image retrieval (DIR). In conventional Bag-of-Visual-Words (BoVW) based document image retrieval method, only SIFT or SURF feature is used to locate feature points and produce a codebook, which has a low discriminative power. Though several multiple feature based BoVW methods are proposed, these methods are based on multiple codebooks. However, some features can not train a codebook, such as connected-component feature. So this paper propose a new multi-feature fusion method, considering these features. Experimental results show that the proposed method has better performance.
机译:随着移动设备的日益普及,近年来目睹了对文档图像检索(DIR)的日益增长的兴趣。在传统的基于视觉词袋(BoVW)的文档图像检索方法中,仅使用SIFT或SURF特征来定位特征点并生成具有低判别力的密码本。尽管提出了几种基于多重特征的BoVW方法,但是这些方法是基于多个码本的。但是,某些功能无法训练代码本,例如连接组件功能。因此,考虑到这些特征,本文提出了一种新的多特征融合方法。实验结果表明,该方法具有较好的性能。

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