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Finding logos in real-world images with point-context representation-based region search

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Abstract

Finding logos in the real-world images is a challenging task due to their small size, simple shape, less texture and clutter background. In this paper, through visual logo analysis with different types of features, we propose a novel framework for finding visual logos in the real-world images. First, we exploit the contextual shape and patch information around feature points, merge them into a combined feature representation (point-context). Considering the characteristics of logos, this kind of fusion is an effective enhancement for the discriminability of single point features. Second, to eliminate the interference of the complex and noisy background, we transfer the logo recognition to a region-to-image search problem by segmenting real-world images into region trees. A weak geometric constraint based on regions is encoded into an inverted file structure to accelerate the search process. Third, we apply global features to refine initial results in the re-ranking stage. Finally, we combine each region score both in max-response and accumulate-response mode to obtain the final results. Performances of the proposed approach are evaluated on both our CASIA-LOGO dataset and the standard Flickr logos 27 dataset. Experiments and comparisons show that our approach is superior to the state-of-the-art approaches.

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Acknowledgments

This work was supported by 973 Program (2010CB327905) and National Natural Science Foundation of China (61273034, 61070104, 61005027 and 61272329).

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Authors and Affiliations

  1. National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Jinqiao Wang, Jianlong Fu & Hanqing Lu

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  1. Jinqiao Wang
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  2. Jianlong Fu
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  3. Hanqing Lu
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Correspondence to Jinqiao Wang.

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Wang, J., Fu, J. & Lu, H. Finding logos in real-world images with point-context representation-based region search. Multimedia Systems 21, 301–311 (2015). https://doi.org/10.1007/s00530-013-0349-6

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