A new trademark detection method via trademark confidence score of MSERs

Yang Zheng; Jie Liu; Yuan Zhang; Shuwu Zhang; Qing Li

doi:10.1117/12.2539671

14 August 2019 A new trademark detection method via trademark confidence score of MSERs

Yang Zheng, Jie Liu, Yuan Zhang, Shuwu Zhang, Qing Li

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111792C (2019) https://doi.org/10.1117/12.2539671
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

This paper proposes a new algorithm to provide high quality potential trademark locations for trademark detection. In real-world circumstances, trademark regions often possess some distinctive, invariant and stable properties which can be gained effectively and efficiently by Maximally Stable Extremal Regions (MSERs). Based on this observation, we design Trademark Confidence Score (TCS) for adaptive MSERs in the images. Then a window refinement algorithm is proposed to retain the high-quality candidate windows generated by Selective Search (SS). Experiments on FlickerLogos-27 and our own dataset demonstrate that our algorithm can significantly reduce the number of candidate proposals produced by SS with little sacrifice of recall for trademarks. Moreover, for trademark detection, our algorithm has better performance while reducing the computational cost of detection.

Citation Download Citation

Yang Zheng, Jie Liu, Yuan Zhang, Shuwu Zhang, and Qing Li "A new trademark detection method via trademark confidence score of MSERs", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111792C (14 August 2019); https://doi.org/10.1117/12.2539671

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