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Content-Based Image Retrieval Using Salient Points and  Spatial Distribution

机译:使用显着点和空间分布的基于内容的图像检索

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In content-based image retrieval, the method based on salient points detection is one of the most active research areas for it can represent the local properties of the image. This paper proposes an improved salient points detector based on wavelet transform which can extract salient points more exactly. Then, an annular segmentation algorithm based on salient points distribution is designed, which takes not only the local image features into account, but also the spatial distribution information of the salient points. Color moments and Gabor features of the regions around the salient points in every annular region were computed as a features vector used for indexing the image. We tested the proposed scheme using a wide range image samples from the Corel Image Library, the experimental results indicating that the method has produced promising results.
机译:在基于内容的图像检索中,基于显着点检测的方法可以代表图像的局部特性,因此是最活跃的研究领域之一。提出了一种改进的基于小波变换的凸点检测器,可以更精确地提取凸点。然后,设计了一种基于显着点分布的环形分割算法,该算法不仅考虑了局部图像特征,还考虑了显着点的空间分布信息。计算每个环形区域中凸点周围区域的色矩和Gabor特征,作为用于索引图像的特征向量。我们使用来自Corel图像库的宽范围图像样本测试了所提出的方案,实验结果表明该方法已产生了令人鼓舞的结果。

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