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Image Retrieval Based on the Local Multi-Features Statistical Method

机译:基于局部多特征统计方法的图像检索

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The spatial geometrical features of the objects are widely used in the image matching and retrieval. The popular algorithms of the spatial feature detection are designed for gray images, which failed to make use of the color information in color images. However, the color information is absolutely nontrivial in discrimination of different objects, vacancy of which would lead to miss judgment. Based on the illumination model, a matching algorithm using the combined color and spatial features is proposed to extract the local invariant features of the objects in this paper. The robust of our algorithm is strengthened and the time-consuming in matching is reduced compared to SIFT algorithm.
机译:对象的空间几何特征在图像匹配和检索中得到了广泛的应用。流行的空间特征检测算法是为灰色图像设计的,该算法无法利用彩色图像中的颜色信息。然而,颜色信息在区分不同物体方面绝对是不平凡的,其空缺会导致判断失误。基于光照模型,提出了一种结合颜色和空间特征的匹配算法,以提取物体的局部不变特征。与SIFT算法相比,我们算法的鲁棒性得到了增强,匹配的时间也减少了。

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