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An improved SIFT algorithm for infringement retrieval
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DOI：10.1007/s11042-017-5060-8.png)
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Abstract
En 中文
To achieve powerful infringement retrieval for reference images in digital publications, a new improved Scale Invariant Feature Transformation (SIFT) algorithm has been proposed in this paper. The retrieval process in the improved algorithm is innovatively divided into two stages to achieve coarse retrieval and fine retrieval respectively. In coarse retrieval, Geographical Statistics (GeoStat) is creatively used to describe the global spatial relationship of key-points in different orientations in an image and then generate a 144-dimensional feature vector to represent each image. In fine retrieval, only partial images, which are highly similar to the query image obtained from results of coarse retrieval, need to be considered. And the indexing and matching process in the improved algorithm is improved by adding a judgment process to improve the matching speed and reduce the mistaken matching rate. Experimental results show that the proposed algorithm has more advantages in retrieval speed and higher retrieval accuracy than the original SIFT algorithm. And the proposed algorithm is also more suitable for infringement retrieval of reference images in digital publications than the original one.
Keywords:
Infringement retrieval
Scale Invariant Feature Transformation ( SIFT)
Geographical Statistics (GeoStat)
coarse-to-fine retrieval
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