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Multiresolution Image Retrieval Using B-splines

机译:使用B样品的多分辨率图像检索

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We propose a technique to search through large image collections. Each database image is stored as a combination of potential query terms (i.e., objects, texture regions, etc.) and non-query terms. The query terms are represented by affine-invariant B-spline moments and wavelet transform subbands. The dual representation supports a two-stage image retrieval system. A user-posed query is first mapped to a dictionary of prototype object contours represented by B-spline moments. The B-spline mapping reduces the query search space to a subset of the original database. Furthermore, it provides an estimate of the affine transformation between the query and the prototypes. The second stage consists of a set of embedded VQ dictionaries of multiresolution subbands of image objects. The estimated affine transformation is employed as a correction factor for the multiresolution VQ mapping. A simple bit string matching algorithm compares the resulting query VQ codewords with the codewords of the database images for retrieval.
机译:我们提出了一种通过大图像集合搜索的技术。每个数据库图像都被存储为潜在查询术语(即,对象,纹理区域等)和非查询术语的组合。查询术语由仿射不变的B样条矩和小波变换子带表示。双表示支持两级图像检索系统。首先将用户构成的查询映射到由B样条矩表示的原型对象轮廓字典。 B样条映射将查询搜索空间减少到原始数据库的子集。此外,它提供了查询与原型之间的仿射变换的估计。第二阶段包括图像对象的多分辨率子带的一组嵌入式VQ词典。估计的仿射变换用作多分辨率VQ映射的校正因子。简单的位字符串匹配算法将生成的查询VQ码字与数据库映像的码字进行比较,以进行检索。

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