Windsurf:基于小波的区域图像检索

Stefania Ardizzoni, Ilaria Bartolini, M. Patella
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引用次数: 124

摘要

在本文中,我们提出了一种基于内容的图像检索的新方法WINDSURF(基于小波的图像索引使用区域碎片)。该方法使用小波变换从图像中提取颜色和纹理特征,并应用聚类技术将图像划分为一组“均匀”区域。利用Bhattacharyya距离对区域描述符进行比较,然后在图像级上将结果进行组合,从而评估图像之间的相似性。在10000张通用图像的测试平台上的实验结果表明,我们的方法在检索与查询图像“语义”相似的图像方面非常有效。特别是,我们将WINDSURF的结果与Stricker和Orengo的方法进行了比较,结果的质量有了明显的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Windsurf: region-based image retrieval using wavelets
In this paper we present WINDSURF (Wavelet-Based Indexing of Images Using Region Fragmentation), a new approach to content-based image retrieval. The method uses the wavelet transform to extract color and texture features from an image and applies a clustering technique to partition the image into a set of "homogeneous" regions. Similarity between images is assessed by using the Bhattacharyya distance to compare region descriptors, and then combining the results at image level. Experimental results on a testbed of 10000 general-purpose images show that our approach is very effective in retrieving images that are "semantically" similar to the query image. In particular, we compared results of WINDSURF with the approach by Stricker and Orengo, showing that that a significant improvement is obtained in the quality of the result.
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