Image retrieval based on Gaussian Mixture Model

Fan-Hui Kong
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引用次数: 3

Abstract

This paper presents some explorations and studies on image retrieval. Firstly, RGB color space is converted to HSV color space for feature extraction. Then, the texture features are obtained by using wavelet, which are combined with some color features based on wavelet transform. Finally, the multi-features generated by Gaussian Mixture Model (GMM) are employed to an image retrieval algorithm. The experimental results on an image database show the effectiveness and competitive performance of the GMM-based image retrieval algorithm.
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基于高斯混合模型的图像检索
本文对图像检索进行了一些探索和研究。首先将RGB色彩空间转换为HSV色彩空间进行特征提取;然后,利用小波变换将纹理特征与基于小波变换的颜色特征相结合,得到纹理特征;最后,将高斯混合模型(GMM)生成的多特征用于图像检索算法。在图像数据库上的实验结果表明了基于gmm的图像检索算法的有效性和竞争力。
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