基于颜色描述符均值偏移聚类的图像检索

Mohamed Ali Bouker, É. Hervet
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引用次数: 3

摘要

基于内容的图像索引包括从数字图像中提取视觉信息(如像素、颜色、物体、形状等),可以由计算机自动快速地完成。这项工作的重点是图像的颜色索引。使用一种称为Mean-Shift的统计算法将图像的颜色分布建模为二维高斯核。在COIL1数据库上进行了实验,结果表明该方法与其他基于内容的检索方法相比效果良好。
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Image retrieval based on mean-shift clustering using color descriptor
Content-based indexing of images consists in extracting visual information from digital images (such as pixels, colors, objects, shapes, etc.), and can be performed automatically and fast by computers. This work focuses on color indexing of images. A statistical algorithm called Mean-Shift is used to modelize the color distributions of images as two-dimensional Gaussian kernels. The experiments have been performed on the COIL1 database and the results show that the proposed method compares well to other content-based retrieval methods.
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