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Tree Representation and Feature Fusion Based Method for Multi-object Binary Image Retrieval

机译:基于树表示和特征融合的多目标二值图像检索方法

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The images with multi-objects are common in multimedia information, such as trademark, symbol and medical image. However state of the art image retrieval systems designed specially for multi-object images are rare. This paper proposes an effective solution for multi-object binary images retrieval by fusing several features. We first employ a Tree Representation Model (TRM) to describe the topology-structure of multi-object binary images. Secondly, we propose two new descriptors to describe the density and the spatial location feature of the objects, respectively. In addition, we combine two descriptors and shape feature to distinguish the difference of the image objects. Finally, the similar matching algorithm based on TRM is given and applied to trademark database retrieval. Experiment shows our method is superior to previous methods in search similar binary images with multi-objects.
机译:具有多对象的图像在商标信息,符号和医学图像等多媒体信息中很常见。但是,专门为多目标图像设计的最新图像检索系统很少。本文提出了一种融合多特征的有效的多目标二值图像检索解决方案。我们首先采用树表示模型(TRM)来描述多对象二进制图像的拓扑结构。其次,我们提出了两个新的描述符来分别描述物体的密度和空间位置特征。另外,我们结合了两个描述符和形状特征来区分图像对象的差异。最后,给出了基于TRM的相似匹配算法,并将其应用于商标数据库检索。实验表明,在多目标相似二值图像搜索中,我们的方法优于以前的方法。

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