基于轮廓的图像检索
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Supported by the National Natural Science Foundation of China under Grant Nos.60435010, 90604017, 60675010 (国家自然科学基金); the National High-Tech Research and Development Plan of China under Grant No.2006AA01Z128 (国家高技术研究发展计划(863)); the National Basic Research Program of China under Grant No.2003CB317004 (国家重点基础研究发展计划(973)); the Natural Science Foundation of Beijing of China under Grant No.4052025 (北京市自然科学基金)


Image Retrieval Based on Contour
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    摘要:

    提出了一种针对多纹理图像的基于轮廓和纹理分割的检索策略.首先提取一幅图像中各个纹理基元的轮廓,计算轮廓的Fourier形状描绘子,根据形状描绘子对轮廓聚类分组.此时,原图像被分割成几组不同形状的纹理基元轮廓,采用Gabor小波变换分别提取各组纹理基元轮廓的特征,从而将原图像表示为Gabor小波特征空间中的特征点集.最后,采用对噪音不敏感的改进Hausdorff距离计算各特征点集之间的距离,便可实现多纹理图像的检索.与已有方法相比,实验结果表明,该方法具有更好的检索精度.

    Abstract:

    This paper proposes a strategy for retrieving multi-texture images based on contour and texture segmentation. Firstly, the contour of each texture primitive is extracted from an image and its Fourier descriptor is calculated. Thus, the contours of the texture primitives in the original image are clustered according to these shape descriptors. Then Gabor wavelet transform is applied to extract the features of texture primitives for each group, so the image can be represented by a set of feature vectors in feature space. Finally, an improved and noise insensitive Hausdorff distance is used to calculate the distance between two feature vector sets. Furthermore, the retrieval of multi-texture images can be implemented. A large amount of experiments show that this method has higher retrieval precision, compared with the state-of-arts methods.

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张志勇,施智平,石志伟,史忠植.基于轮廓的图像检索.软件学报,2008,19(9):2461-2470

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  • 收稿日期:2006-12-12
  • 最后修改日期:2007-06-14
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