Content-Based Image Retrieval Using Wavelet Spatial-Color and Gabor Normalized Texture in Multi-resolution Database

Yong-Hwan Lee, Sang-Burm Rhee, Bonam Kim
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引用次数: 22

Abstract

Image retrieval is one of the most exciting and fastest growing research areas in the field of multimedia technology. This paper proposes a new efficient image retrieval method that applies a weighted combination of color and texture to the wavelet transform, based on spatial-color and second order statistics, respectively. To evaluate the performance of the proposed algorithm, we assess the simulation's performance in terms of average precision and Fscore using several image databases, and perform comparative analysis with existing methods such as MPEG-7. The experimental results show that the proposed approach significantly improves the effectiveness of image retrieval. The proposed descriptor is particularly useful for multi-resolution image search and retrieval.
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基于小波空间颜色和Gabor归一化纹理的多分辨率数据库图像检索
图像检索是多媒体技术领域中最令人兴奋和发展最快的研究领域之一。本文提出了一种基于空间颜色统计量和二阶统计量的图像检索方法,该方法将颜色和纹理的加权组合应用于小波变换。为了评估所提出算法的性能,我们使用多个图像数据库评估了模拟的平均精度和Fscore性能,并与现有方法(如MPEG-7)进行了比较分析。实验结果表明,该方法显著提高了图像检索的有效性。所提出的描述符对于多分辨率图像的搜索和检索特别有用。
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