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Proceedings Paper

A new trademark detection method via trademark confidence score of MSERs
Author(s): Yang Zheng; Jie Liu; Yuan Zhang; Shuwu Zhang; Qing Li
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Paper 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.

Paper Details

Date Published: 14 August 2019
PDF: 7 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111792C (14 August 2019); doi: 10.1117/12.2539671
Show Author Affiliations
Yang Zheng, Institute of Automation (China)
Jie Liu, Institute of Automation (China)
Yuan Zhang, Institute of Automation (China)
Shuwu Zhang, Institute of Automation (China)
Qing Li, Univ. of Science and Technology Beijing (China)

Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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