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Combining pixel domain and compressed domain index for sketch based image retrieval

机译:结合像素域和压缩域索引以进行基于草图的图像检索

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摘要

Sketch-based image retrieval (SBIR) lets one express a precise visual query with simple and widespread means. In the SBIR approaches, the challenge consists in representing the image dataset features in a structure that allows one to efficiently and effectively retrieve images in a scalable system. We put forward a sketch-based image retrieval solution where sketches and natural image contours are represented and compared, in both, the compressed-domain of wavelet and in the pixel domain. The query is efficiently performed in the wavelet domain, while effectiveness refinements are achieved using the pixel domain to verify the spatial consistency between the sketch strokes and the natural image contours. Also, we present an efficient scheme of inverted lists for sketch-based image retrieval using the compressed-domain of wavelets. Our proposal of indexing presents two main advantages, the amount of the data to compute the query is smaller than the traditional method while it presents a better effectiveness.
机译:基于草图的图像检索(SBIR)使人们可以用简单且广泛的方式表达精确的视觉查询。在SBIR方法中,挑战在于以一种结构表示图像数据集的特征,该结构允许人们在可伸缩系统中高效地检索图像。我们提出了一种基于草图的图像检索解决方案,其中在小波的压缩域和像素域中都表示和比较了草图和自然图像轮廓。在小波域中可以有效地执行查询,而使用像素域可以验证草图笔划和自然图像轮廓之间的空间一致性,从而提高效率。同样,我们提出了一种有效的倒排列表方案,用于使用小波的压缩域进行基于草图的图像检索。我们提出的索引建议具有两个主要优点,即用于计算查询的数据量比传统方法小,同时具有更好的有效性。

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